SlideShare a Scribd company logo
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012
DOI : 10.5121/ijcseit.2012.2306 81
ANTI-SYNCHRONIZATION OF HYPERCHAOTIC BAO
AND HYPERCHAOTIC XU SYSTEMS VIA
ACTIVE CONTROL
Sundarapandian Vaidyanathan
1
Research and Development Centre, Vel Tech Dr. RR & Dr. SR Technical University
Avadi, Chennai-600 062, Tamil Nadu, INDIA
sundarvtu@gmail.com
Abstract
This paper investigates the anti-synchronization of identical hyperchaotic Bao systems (Bao and Liu,
2008), identical hyperchaotic Xu systems (Xu, Cai and Zheng, 2009) and non-identical hyperchaotic Bao
and hyperchaotic Xu systems. Active nonlinear control has been deployed for the anti- synchronization of
the hyperchaotic systems addressed in this paper and the main results have been established using
Lyapunov stability theory. Since the Lyapunov exponents are not required for these calculations, the active
nonlinear control method is very effective and convenient to achieve anti-synchronization of identical and
non-identical hyperchaotic Bao and hyperchaotic Xu systems. Numerical simulations have been provided to
validate and demonstrate the effectiveness of the anti-synchronization results for the hyperchaotic Cao and
hyperchaotic Xu systems.
KEYWORDS
Active Control, Anti-Synchronization, Hyperchaos, Hyperchaotic Bao System, Hyperchaotic Xu System.
1. INTRODUCTION
Chaos is a complex nonlinear phenomenon. The first chaotic attractor was discovered by Lorenz
([1], 1963), when he was studying the atmospheric convection in the weather models. Since then,
chaos has been received extensive investigations and chaos phenomenon has been observed in a
variety of fields including physical systems [2], chemical systems [3], ecological systems [4],
secure communications [5-6], etc.
The seminal work on chaos synchronization problem was published by Pecora and Carroll ([7],
1990). From then on, chaos synchronization has been extensively and intensively studied in the
last three decades [8-30].
In most of the anti-synchronization approaches, the master-slave or drive-response formalism is
used. If a particular chaotic system is called the master or drive system and another chaotic
system is called the slave or response system, then the idea of anti-synchronization is to use the
output of the master system to control the slave system so that the states of the slave system have
the same amplitude but opposite signs as the states of the master system asymptotically. Thus,
when anti-synchronization is achieved, the sum of the states of the master and slave systems tends
to zero asymptotically with time.
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012
82
In the recent years, various schemes have been deployed for chaos synchronization such as PC
method [2], OGY method [8], active control [9-12], adaptive control [13-15], backstepping
design [16], sampled-data feedback [17], sliding mode control [18-20], etc. Recently, active
control method has been applied to achieve anti-synchronization of two identical chaotic systems
[21-22].
Hyperchaotic system is usually defined as a chaotic system with at least two positive Lyapunov
exponents, implying that its dynamics are expanded in several different directions simultaneously.
Thus, the hyperchaotic systems have more complex dynamical behaviour which can be used to
improve the security of a chaotic communication system. Hence, the theoretical design and circuit
realization of various hyperchaotic signals have become important research topics [23-27].
In this paper, we use active control to derive new results for the anti-synchronization of identical
hyperchaotic Bao systems ([28], 2008), identical hyperchaotic Xu systems ([29], 2009) and non-
identical hyperchaotic Bao and hyperchaotic Xu systems.
This paper is organized as follows. In Section 2, we describe the problem statement and our
methodology using Lyapunov stability theory. In Section 3, we provide a description of the
hyperchaotic systems addressed in this paper. In Section 4, we discuss the anti-synchronization of
identical hyperchaotic Bao systems (2008) using active nonlinear control. In Section 5, we
discuss the anti-synchronization of identical hyperchaotic Xu systems (2009) using active
nonlinear control. In Section 6, we discuss the anti-synchronization of hyperchaotic Bao and
hyperchaotic Xu systems using active nonlinear control. In Section 7, we summarize the main
results obtained in this paper.
2. PROBLEM STATEMENT AND OUR METHODOLOGY
As the master or drive system, we consider the chaotic system described by
( ),x Ax f x= +& (1)
where n
x∈R is the state vector, A is the n n× matrix of system parameters and : n n
f →R R is
the nonlinear part of the system.
As the slave or response system, we consider the following chaotic system described by
( ) ,y By g y u= + +& (2)
where n
y ∈R is the state of the slave system, B is the n n× matrix of system parameters,
: n n
g →R R is the nonlinear part of the system and u is the active controller to be designed.
If A B= and ,f g= then x and y are the states of two identical chaotic systems. If A B≠ or
,f g≠ then x and y are the states of two different chaotic systems.
For the anti-synchronization of the chaotic systems (1) and (2) using active control, we design a
state feedback controller ,u which anti-synchronizes the states of the master system (1) and the
slave system (2) for all initial conditions (0), (0) .n
x y ∈R
Thus, we define the anti-synchronization error as
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012
83
,e y x= + (3)
Hence, the error dynamics is obtained as
( ) ( )e By Ax g y f x u= + + + +& (4)
Thus, the anti-synchronization problem is essentially to find a feedback controller (active
controller) u so as to stabilize the error dynamics (4) for all initial conditions, i.e.
lim ( ) 0,
t
e t
→∞
= for all (0) n
e ∈R (5)
We use the Lyapunov stability theory as our methodology.
We take as a candidate Lyapunov function
( ) ,T
V e e Pe= (6)
where P is a positive definite matrix. Note that : n
V R→R is a positive definite function by
construction.
If we find a feedback controller u so that
( ) ,T
V e e Qe= −& (7)
where Q is a positive definite matrix, then : n
V →& R R is a negative definite function.
Thus, by Lyapunov stability theory [25], the error dynamics (4) is globally exponentially stable.
Hence, the states of the master system (1) and the slave system (2) will be globally and
exponentially anti-synchronized for all values of the initial conditions (0), (0) .n
x y ∈R
3. SYSTEMS DESCRIPTION
The hyperchaotic Bao system ([28], 2008) is described by the 4D dynamics
1 2 1 4
2 2 1 3
3 1 2 3
4 1 2 3
( )x a x x x
x cx x x
x x x bx
x x dx xε
= − +
= −
= −
= +
&
&
&
&
(8)
where 1 2 3 4, , ,x x x x are the state variables and , , , ,a b c d ε are positive constants.
The four-dimensional Bao system (8) is hyperchaotic when
36, 3, 20, 0.1a b c d= = = = and 21.ε =
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012
84
The phase portrait of the hyperchaotic Bao system is shown in Figure 1.
Figure 1. Phase Portrait of the Hyperchaotic Bao System
The hyperchaotic Xu system ([29], 2009) is described by the 4D dynamics
1 2 1 4
2 1 1 3
3 3 1 2
4 1 3 2
( )x x x x
x x rx x
x x lx x
x x x mx
α
β
γ
= − +
= +
= − −
= −
&
&
&
&
(9)
where 1 2 3 4, , ,x x x x are the state variables and , , , ,l mα β γ are positive constants.
The four-dimensional Xu system (9) is hyperchaotic when
10, 40, 2.5, 16, 1r lα β γ= = = = = and 2.m =
The phase portrait of the hyperchaotic Xu system is shown in Figure 2.
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012
85
Figure 2. Phase Portrait of the Hyperchaotic Xu System
3. ANTI-SYNCHRONIZATION OF HYPERCHAOTIC BAO SYSTEMS
In this section, we discuss the anti-synchronization of identical hyperchaotic Bao systems ([28],
2008).
As the master system, we consider the hyperchaotic Bao system described by
1 2 1 4
2 2 1 3
3 1 2 3
4 1 2 3
( )x a x x x
x cx x x
x x x bx
x x dx xε
= − +
= −
= −
= +
&
&
&
&
(10)
where 1 2 3 4, , ,x x x x are the state variables and , , , ,a b c d ε are positive constants.
As the slave system, we consider the controlled hyperchaotic Bao dynamics described by
1 2 1 4 1
2 2 1 3 2
3 1 2 3 3
4 1 2 3 4
( )y a y y y u
y cy y y u
y y y by u
y y dy y uε
= − + +
= − +
= − +
= + +
&
&
&
&
(11)
where 1 2 3 4, , ,y y y y are the state variables and 1 2 3 4, , ,u u u u are the active controls.
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012
86
The anti-synchronization error is defined as
1 1 1
2 2 2
3 3 3
4 4 4
e y x
e y x
e y x
e y x
= +
= +
= +
= +
(12)
A simple calculation gives the error dynamics
1 2 1 4 1
2 2 1 3 1 3 2
3 3 1 2 1 2 3
4 1 2 3 2 3 4
( )
( )
e a e e e u
e ce y y x x u
e be y y x x u
e e d y y x x uε
= − + +
= − − +
= − + + +
= + + +
&
&
&
&
(13)
We consider the active nonlinear controller defined by
1 2 1 4 1 1
2 2 1 3 1 3 2 2
3 3 1 2 1 2 3 3
4 1 2 3 2 3 4 4
( )
( )
u a e e e k e
u ce y y x x k e
u be y y x x k e
u e d y y x x k eε
= − − − −
= − + + −
= − − −
= − − + −
(14)
where 1 2 3 4, , ,k k k k are positive constants.
Substitution of (14) into (13) yields the linear error dynamics
1 1 1 2 2 2 3 3 3 4 4 4, , ,e k e e k e e k e e k e= − = − = − = −& & & & (15)
We consider the quadratic Lyapunov function defined by
( )2 2 2 2
1 2 3 4
1 1
( ) ,
2 2
T
V e e e e e e e= = + + + (16)
which is a positive definite function on 4
.R
Next, we establish the main result of this section using Lyapunov stability theory.
Theorem 1. The identical hyperchaotic Bao systems (10) and (11) are globally and
exponentially anti-synchronized with the active nonlinear controller (13).
Proof. Differentiating (16) along the trajectories of the error system (15), we get
2 2 2 2
1 1 2 2 3 3 4 4( ) ,V e k e k e k e k e= − − − −& (17)
which is a negative definite function on 4
R
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012
87
Thus, by Lyapunov stability theory [30], the error dynamics (15) is globally
exponentially stable. This completes the proof.
Numerical Simulations:
For the numerical simulations, the fourth order Runge-Kutta method with initial time-step
8
10h −
= is used to solve the two systems of differential equations (10) and (11) with the
active nonlinear controller (14). We take the gains as 5ik = for 1,2,3,4.i =
The parameters of the identical hyperchaotic Bao systems (8) and (9) are selected as
36, 3, 20, 0.1a b c d= = = = and 21.ε =
The initial values for the master system (8) are taken as
1 2 3 4(0) 5, (0) 2, (0) 14, (0) 20x x x x= = − = =
and the initial values for the slave system (9) are taken as
1 2 3 4(0) 24, (0) 17, (0) 18, (0) 22y y y y= = = − = −
Figure 4 depicts the anti-synchronization of the identical hyperchaotic Bao systems (10) and (11).
Figure 4 depicts the time-history of the anti-synchronization error.
Figure 3. Anti-Synchronization of Identical Hyperchaotic Bao Systems
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012
88
Figure 4. Time-History of Anti-Synchronization Error 1 2 3 4, , ,e e e e
4. ANTI-SYNCHRONIZATION OF HYPERCHAOTIC XU SYSTEMS
In this section, we discuss the anti-synchronization of identical hyperchaotic Xu systems ([29],
2009).
As the master system, we consider the hyperchaotic Xu system described by
1 2 1 4
2 1 1 3
3 3 1 2
4 1 3 2
( )x x x x
x x rx x
x x lx x
x x x mx
α
β
γ
= − +
= +
= − −
= −
&
&
&
&
(18)
where 1 2 3 4, , ,x x x x are the state variables and , , , , ,r l mα β γ are positive constants.
As the slave system, we consider the controlled hyperchaotic Xu dynamics described by
1 2 1 4 1
2 1 1 3 2
3 3 1 2 3
4 1 3 2 4
( )y y y y u
y y ry y u
y y ly y u
y y y my u
α
β
γ
= − + +
= + +
= − − +
= − +
(19)
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012
89
where 1 2 3 4, , ,y y y y are the state variables and 1 2 3 4, , ,u u u u are the active controls.
The anti-synchronization error is defined as
1 1 1
2 2 2
3 3 3
4 4 4
e y x
e y x
e y x
e y x
= +
= +
= +
= +
(20)
A simple calculation gives the error dynamics
1 2 1 4 1
2 1 1 3 1 3 2
3 3 1 2 1 2 3
4 2 1 3 1 3 4
( )
( )
( )
e e e e u
e e r y y x x u
e e l y y x x u
e me y y x x u
α
β
γ
= − + +
= + + +
= − − + +
= − + + +
&
&
&
&
(21)
We consider the active nonlinear controller defined by
1 2 1 4 1 1
2 1 1 3 1 3 2 2
3 3 1 2 1 2 3 3
4 2 1 3 1 3 4 4
( )
( )
( )
u e e e k e
u e r y y x x k e
u e l y y x x k e
u me y y x x k e
α
β
γ
= − − − −
= − − + −
= + + −
= − − −
(22)
where 1 2 3 4, , ,k k k k are positive constants.
Substitution of (22) into (21) yields the linear error dynamics
1 1 1 2 2 2 3 3 3 4 4 4, , ,e k e e k e e k e e k e= − = − = − = −& & & & (23)
We consider the quadratic Lyapunov function defined by
( )2 2 2 2
1 2 3 4
1 1
( ) ,
2 2
T
V e e e e e e e= = + + + (24)
which is a positive definite function on 4
.R
Next, we establish the main result of this section using Lyapunov stability theory.
Theorem 2. The identical hyperchaotic Xu systems (18) and (19) are globally and
exponentially anti-synchronized with the active nonlinear controller (22).
Proof. Differentiating (16) along the trajectories of the error system (15), we get
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012
90
2 2 2 2
1 1 2 2 3 3 4 4( ) ,V e k e k e k e k e= − − − −& (25)
which is a negative definite function on 4
R
Thus, by Lyapunov stability theory [30], the error dynamics (23) is globally
exponentially stable.
Hence, the states of the identical hyperchaotic Xu systems (18) and (19) are globally and
exponentially anti-synchronized for all initial conditions (0), (0) .n
x y ∈R
This completes the proof.
Numerical Simulations:
For the numerical simulations, the fourth order Runge-Kutta method with initial time-step
6
10h −
= is used to solve the two systems of differential equations (18) and (19) with the
active nonlinear controller (22).
We take the feedback gains as
1 2 3 45, 5, 5, 5k k k k= = = =
The parameters of the identical hyperchaotic Xu systems (18) and (19) are selected as
10, 40, 2.5, 16, 1r lα β γ= = = = = and 2.m =
The initial values for the master system (18) are taken as
1 2 3 4(0) 12, (0) 14, (0) 7, (0) 21x x x x= = − = − =
and the initial values for the slave system (19) are taken as
1 2 3 4(0) 26, (0) 10, (0) 18, (0) 4y y y y= = = = −
Figure 5 depicts the anti-synchronization of the identical hyperchaotic Xu systems (18) and (19).
Figure 6 depicts the time-history of the anti-synchronisation error 1 2 3 4, , , .e e e e
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012
91
Figure 5. Anti-Synchronization of Identical Hyperchaotic Xu Systems
Figure 6. Time-History of the Anti-Synchronization Error 1 2 3 4, , ,e e e e
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012
92
5. ANTI-SYNCHRONIZATION OF HYPERCHAOTIC BAO AND
HYPERCHAOTIC XU SYSTEMS
In this section, we consider the anti-synchronization of non-identical hyperchaotic Bao system
([28], 2008) and hyperchaotic Xu system ([29], 2009).
As the master system, we consider the hyperchaotic Bao system described by
1 2 1 4
2 2 1 3
3 1 2 3
4 1 2 3
( )x a x x x
x cx x x
x x x bx
x x dx xε
= − +
= −
= −
= +
&
&
&
&
(26)
where 1 2 3 4, , ,x x x x are the state variables and , , , ,a b c d ε are positive constants.
As the slave system, we consider the controlled hyperchaotic Xu dynamics described by
1 2 1 4 1
2 1 1 3 2
3 3 1 2 3
4 1 3 2 4
( )y y y y u
y y ry y u
y y ly y u
y y y my u
α
β
γ
= − + +
= + +
= − − +
= − +
(27)
where 1 2 3 4, , ,y y y y are the state variables, , , , , ,r l mα β γ are positive constants and
1 2 3 4, , ,u u u u are the active controls.
The anti-synchronization error is defined as
1 1 1
2 2 2
3 3 3
4 4 4
e y x
e y x
e y x
e y x
= +
= +
= +
= +
(28)
A simple calculation gives the error dynamics
1 2 1 4 2 1 1
2 1 1 2 1 3 1 3 2
3 3 3 1 2 1 2 3
4 2 1 2 1 3 2 3 4
( ) ( )( )
( )
e e e e a x x u
e e x cx ry y x x u
e e b x ly y x x u
e me x mx y y dx x u
α α
β β
γ γ
ε
= − + − − − +
= − + + − +
= − − − − + +
= − + + + + +
&
&
&
&
(29)
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012
93
We consider the active nonlinear controller defined by
1 2 1 4 2 1 1 1
2 1 1 2 1 3 1 3 2 2
3 3 3 1 2 1 2 3 3
4 2 1 2 1 3 2 3 4 4
( ) ( )( )
( )
u e e e a x x k e
u e x cx ry y x x k e
u e b x ly y x x k e
u me x mx y y dx x k e
α α
β β
γ γ
ε
= − − − + − − −
= − + − − + −
= + − + − −
= − − − − −
(30)
Substitution of (30) into (29) yields the linear error dynamics
1 1 1
2 2 2
3 3 3
4 4 4
e k e
e k e
e k e
e k e
= −
= −
= −
= −
&
&
&
&
(31)
We consider the quadratic Lyapunov function defined by
( )2 2 2 2
1 2 3 4
1 1
( ) ,
2 2
T
V e e e e e e e= = + + + (32)
which is a positive definite function on 4
.R
Next, we establish the main result of this section using Lyapunov stability theory.
Theorem 3. The non-identical hyperchaotic Bao system (26) and hyperchaotic Xu system
(27) are globally and exponentially anti-synchronized with the active nonlinear
controller (29).
Proof. Differentiating (32) along the trajectories of the error system (31), we get
2 2 2 2
1 1 2 2 3 3 4 4( ) ,V e k e k e k e k e= − − − −& (33)
which is a negative definite function on 4
R since α and γ are positive constants.
Thus, by Lyapunov stability theory [30], the error dynamics (31) is globally
exponentially stable.
Hence, it follows that the states of the hyperchaotic Bao system (26) and hyperchaotic Xu
system (27) are globally and exponentially anti-synchronized for all initial conditions
(0), (0) .n
x y ∈R
This completes the proof.
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012
94
Numerical Simulations
For the numerical simulations, the fourth order Runge-Kutta method with initial time-step
6
10h −
= is used to solve the two systems of differential equations (26) and (27) with the
active nonlinear controller (30).
We take the feedback gains as
1 2 35, 5, 5k k k= = = and 4 5.k =
The parameters of the identical hyperchaotic Bao system (24) are selected as
36, 3, 20, 0.1a b c d= = = = and 21.ε =
The parameters of the identical hyperchaotic Xu system (25) are selected as
10, 40, 2.5, 16, 1r lα β γ= = = = = and 2.m =
The initial values for the master system (26) are taken as
1 2 3 4(0) 25, (0) 6, (0) 9, (0) 14x x x x= = − = = −
and the initial values for the slave system (27) are taken as
1 2 3 4(0) 12, (0) 15, (0) 20, (0) 8y y y y= = = − = −
Figure 7 depicts the anti-synchronization of the non-identical hyperchaotic systems, viz.
hyperchaotic Bao system (26) and hyperchaotic Xu system (28).
Figure 8 depicts the time-history of the anti-synchronization error.
6. CONCLUSIONS
In this paper, using the active control method, new results have been derived for the anti-
synchronization for the following pairs of hyperchaotic systems:
(A) Identical hyperchaotic Bao systems (2008)
(B) Identical hyperchaotic Xu systems (2009)
(C) Non-identical hyperchaotic Bao and hyperchaotic Xu systems.
The anti-synchronization results derived in this paper have been proved using Lyapunov stability
theory. Since the Lyapunov exponents are not required for these calculations, the active control
method is very convenient and efficient for the anti- synchronization of identical and non-
identical hyperchaotic Bao and hyperchaotic Xu systems. Numerical simulation results have been
presented to illustrate the anti-synchronization results derived in this paper.
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012
95
Figure 7. Anti-Synchronization of Hyperchaotic Bao and Hyperchaotic Xu Systems
Figure 8. Time-History of the Anti-Synchronization Error 1 2 3 4, , ,e e e e
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012
96
REFERENCES
[1] Lorenz, E.N. (1963) “Deterministic nonperiodic flow”, J. Atmos. Sci., Vol. 20, pp 130-141.
[2] Lakshmanan, M. & Murali, K. (1996) Nonlinear Oscillators: Controlling and Synchronization,
World Scientific, Singapore.
[3] Han, S.K., Kerrer, C. & Kuramoto, Y. (1995) “Dephasing and burstling in coupled neural oscillators”,
Phys. Rev. Lett., Vol. 75, pp 3190-3193.
[4] Blasius, B., Huppert, A. & Stone, L. (1999) “Complex dynamics and phase synchronization in
spatially extended ecological system”, Nature, Vol. 399, pp 354-359.
[5] Feki, M. (2003) “An adaptive chaos synchronization scheme applied to secure communication”,
Chaos, Solitons and Fractals, Vol. 18, pp 141-148.
[6] Murali, K. & Lakshmanan, M. (1998) “Secure communication using a compound signal from
generalized synchronizable chaotic systems”, Phys. Rev. Lett. A, Vol. 241, pp 303-310.
[7] Pecora, L.M. & Carroll, T.L. (1990) “Synchronization in chaotic systems”, Phys. Rev. Lett., Vol. 64,
pp 821-824.
[8] Ott, E., Grebogi, C. & Yorke, J.A. (1990) “Controlling chaos”, Phys. Rev. Lett., Vol. 64, pp 1196-
1199.
[9] Ho, M.C. & Hung, Y.C. (2002) “Synchronization of two different chaotic systems by using
generalized active control”, Physics Letters A, Vol. 301, pp. 424-428.
[10] Chen, H.K. (2005) “Global chaos synchronization of new chaotic systems via nonlinear control”,
Chaos, Solitons & Fractals, Vol. 23, pp. 1245-1251.
[11] Sundarapandian, V. (2011) “Global chaos synchronization of four-scroll and four-wing chaotic
attractors by active nonlinear control,” International Journal on Computer Science and Engineering,
Vol. 3, No. 5, pp. 2145-2155.
[12] Sundarapandian, V. (2011) “Anti-synchronization of Arneodo and Coullet systems by active
nonlinear control,” International Journal of Control Theory and Applications, Vol. 4, No. 1, pp. 25-
36.
[13] Liao, T.L. & Tsai, S.H. (2000) “Adaptive synchronization of chaotic systems and its applications to
secure communications”, Chaos, Solitons and Fractals, Vol. 11, pp 1387-1396.
[14] Sundarapandian, V. (2011) “Adaptive control and synchronization of hyperchaotic Cai system”,
International Journal of Control Theory and Computer Modelling, Vol. 1, No. 1, pp. 1-13.
[15] Sundarapandian, V. (2011) “Adaptive synchronization of hyperchaotic Lorenz and hyperchaotic Liu
systems”, International Journal of Instrumentation and Control Systems, Vol. 1, No. 1, pp. 1-18.
[16] Yu, Y.G. & Zhang, S.C. (2006) “Adaptive backstepping synchronization of uncertain chaotic
systems”, Chaos, Solitons and Fractals, Vol. 27, pp 1369-1375.
[17] Yang, T. & Chua, L.O. (1999) “Control of chaos using sampled-data feedback control”, Internat. J.
Bifurcat. Chaos, Vol. 9, pp 215-219.
[18] Sundarapandian, V. (2011) “Global chaos synchronization of four-wing chaotic systems by sliding
mode control”, International Journal of Control Theory and Computer Modelling, Vol. 1, No. 1, pp.
15-31.
[19] Sundarapandian, V. (2011) “Global chaos synchronization of Pehlivan systems by sliding mode
control”, International Journal on Computer Science and Engineering, Vol. 3, No. 5, pp. 2163-2169.
[20] Sundarapandian, V. (2011) “Sliding mode controller design for the synchronization of Shimizu-
Morioka chaotic systems”, International Journal of Information Sciences and Techniques, Vol. 1, No.
1, pp 20-29.
[21] Li, G.H. (2005) “Synchronization and anti-synchronization of Colpitts oscillators using active
control,” Chaos, Solitons & Fractals, Vol. 26, pp 87-93.
[22] Hu, J. (2005) “Adaptive control for anti-synchronization of Chua’s chaotic system”, Physics Letters
A, Vol. 339, pp. 455-460.
[23] Rössler, O.E. (1979) “An equation for hyperchaos”, Phys. Letters A, Vol. 71, pp 155-157.
[24] Thamilmaran, K., Lakshmanan, M. & Venkatesan, A. (2004) “A hyperchaos in a modified canonical
Chua’s circuit”, International J. Bifurcat. Chaos, Vol. 14, pp 221-243.
[25] Vicente, R., Dauden, J., Colet, P. & Toral, R. (2005) “Analysis and characterization of the hyperchaos
generated by a semiconductor laser object”, IEEE J. Quantum Electronics, Vol. 41, pp 541-548.
[26] Li, Y., Tang, W.K.S. & Chen, G. (2005) “Generating hyperchaos via state feedback control,”
Internat. J. Bifurcat. Chaos, Vol. 15, No. 10, pp 3367-3375.
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012
97
[27] Wang, J. & Chen, J. (2008) “A novel hyperchaotic system and its complex dynamics”, Internat. J.
Bifurcat. Chaos, Vol. 18, No. 11, pp 3309-3324.
[28] Bao, B.C. & Liu, Z. (2008) “A hyperchaotic attractor coined from the chaotic Lü system”, Chin.
Physics Letters, Vol. 25, pp 2396-2399.
[29] Xu, J., Cai, G. & Zheng, S. (2009) “A novel hyperchaotic system and its control”, J. Uncertain
Systems, Vol. 3, pp 137-144.
[30] Hahn, W. (1967) The Stability of Motion, Springer, New York.
Author
Dr. V. Sundarapandian earned his Doctor of Science degree in Electrical and Systems
Engineering from Washington University, Saint Louis, Missouri, USA. He is currently
Professor in the Research and Development Centre at Vel Tech Dr. RR & Dr. SR
Technical University, Chennai, Tamil Nadu, India. He has published over 260
publications in refereed International journals and over 170 papers in National and
International Conferences. He is the Editor-in-Chief of the AIRCC journals -
International Journal of Instrumentation and Control Systems, International Journal of
Control Systems and Computer Modelling and International Journal of Information
Technology, Control and Automation. His research interests are Linear and Nonlinear Control Systems,
Chaos Theory and Control, Soft Computing, Optimal Control, Process Control, Operations Research,
Mathematical Modelling, Scientific Computing using SCILAB/MATLAB. He has delivered many Keynote
Lectures on Chaos Theory and Control Engineering.

More Related Content

PDF
GLOBAL CHAOS SYNCHRONIZATION OF HYPERCHAOTIC QI AND HYPERCHAOTIC JHA SYSTEMS ...
PDF
ACTIVE CONTROLLER DESIGN FOR THE HYBRID SYNCHRONIZATION OF HYPERCHAOTIC XU AN...
PDF
HYBRID SYNCHRONIZATION OF LIU AND LÜ CHAOTIC SYSTEMS VIA ADAPTIVE CONTROL
PDF
ACTIVE CONTROLLER DESIGN FOR THE HYBRID SYNCHRONIZATION OF HYPERCHAOTIC ZHEN...
PDF
ADAPTIVE CHAOS CONTROL AND SYNCHRONIZATION OF HYPERCHAOTIC LIU SYSTEM
PDF
GLOBAL CHAOS SYNCHRONIZATION OF UNCERTAIN LORENZ-STENFLO AND QI 4-D CHAOTIC S...
PDF
ADAPTIVE STABILIZATION AND SYNCHRONIZATION OF LÜ-LIKE ATTRACTOR
PDF
HYBRID CHAOS SYNCHRONIZATION OF UNCERTAIN LORENZ-STENFLO AND QI 4-D CHAOTIC S...
GLOBAL CHAOS SYNCHRONIZATION OF HYPERCHAOTIC QI AND HYPERCHAOTIC JHA SYSTEMS ...
ACTIVE CONTROLLER DESIGN FOR THE HYBRID SYNCHRONIZATION OF HYPERCHAOTIC XU AN...
HYBRID SYNCHRONIZATION OF LIU AND LÜ CHAOTIC SYSTEMS VIA ADAPTIVE CONTROL
ACTIVE CONTROLLER DESIGN FOR THE HYBRID SYNCHRONIZATION OF HYPERCHAOTIC ZHEN...
ADAPTIVE CHAOS CONTROL AND SYNCHRONIZATION OF HYPERCHAOTIC LIU SYSTEM
GLOBAL CHAOS SYNCHRONIZATION OF UNCERTAIN LORENZ-STENFLO AND QI 4-D CHAOTIC S...
ADAPTIVE STABILIZATION AND SYNCHRONIZATION OF LÜ-LIKE ATTRACTOR
HYBRID CHAOS SYNCHRONIZATION OF UNCERTAIN LORENZ-STENFLO AND QI 4-D CHAOTIC S...

What's hot (19)

PDF
ADAPTIVE CONTROL AND SYNCHRONIZATION OF SPROTT-I SYSTEM WITH UNKNOWN PARAMETERS
PDF
Adaptive Controller Design For The Synchronization Of Moore-Spiegel And Act S...
PDF
ADAPTIVE CONTROL AND SYNCHRONIZATION OF A HIGHLY CHAOTIC ATTRACTOR
PDF
ADAPTIVE CONTROL AND SYNCHRONIZATION OF LIU’S FOUR-WING CHAOTIC SYSTEM WITH C...
PDF
THE DESIGN OF ADAPTIVE CONTROLLER AND SYNCHRONIZER FOR QI-CHEN SYSTEM WITH UN...
PDF
ADAPTIVESYNCHRONIZER DESIGN FOR THE HYBRID SYNCHRONIZATION OF HYPERCHAOTIC ZH...
PDF
ANTI-SYNCHRONIZATION OF HYPERCHAOTIC WANG AND HYPERCHAOTIC LI SYSTEMS WITH UN...
PDF
THE ACTIVE CONTROLLER DESIGN FOR ACHIEVING GENERALIZED PROJECTIVE SYNCHRONIZA...
PDF
ACTIVE CONTROLLER DESIGN FOR THE GENERALIZED PROJECTIVE SYNCHRONIZATION OF TH...
PDF
STATE FEEDBACK CONTROLLER DESIGN FOR THE OUTPUT REGULATION OF SPROTT-H SYSTEM
PDF
ADAPTIVE STABILIZATION AND SYNCHRONIZATION OF HYPERCHAOTIC QI SYSTEM
PDF
ADAPTIVE CONTROLLER DESIGN FOR THE ANTI-SYNCHRONIZATION OF HYPERCHAOTIC YANG ...
PDF
Modified Projective Synchronization of Chaotic Systems with Noise Disturbance,...
PDF
ADAPTIVE CONTROL AND SYNCHRONIZATION OF HYPERCHAOTIC NEWTON-LEIPNIK SYSTEM
PDF
OUTPUT REGULATION OF SHIMIZU-MORIOKA CHAOTIC SYSTEM BY STATE FEEDBACK CONTROL
PDF
STABILITY ANALYSIS AND CONTROL OF A 3-D AUTONOMOUS AI-YUAN-ZHI-HAO HYPERCHAOT...
PDF
An Exponential Observer Design for a Class of Chaotic Systems with Exponentia...
PDF
HYBRID SLIDING SYNCHRONIZER DESIGN OF IDENTICAL HYPERCHAOTIC XU SYSTEMS
PDF
40220140501006
ADAPTIVE CONTROL AND SYNCHRONIZATION OF SPROTT-I SYSTEM WITH UNKNOWN PARAMETERS
Adaptive Controller Design For The Synchronization Of Moore-Spiegel And Act S...
ADAPTIVE CONTROL AND SYNCHRONIZATION OF A HIGHLY CHAOTIC ATTRACTOR
ADAPTIVE CONTROL AND SYNCHRONIZATION OF LIU’S FOUR-WING CHAOTIC SYSTEM WITH C...
THE DESIGN OF ADAPTIVE CONTROLLER AND SYNCHRONIZER FOR QI-CHEN SYSTEM WITH UN...
ADAPTIVESYNCHRONIZER DESIGN FOR THE HYBRID SYNCHRONIZATION OF HYPERCHAOTIC ZH...
ANTI-SYNCHRONIZATION OF HYPERCHAOTIC WANG AND HYPERCHAOTIC LI SYSTEMS WITH UN...
THE ACTIVE CONTROLLER DESIGN FOR ACHIEVING GENERALIZED PROJECTIVE SYNCHRONIZA...
ACTIVE CONTROLLER DESIGN FOR THE GENERALIZED PROJECTIVE SYNCHRONIZATION OF TH...
STATE FEEDBACK CONTROLLER DESIGN FOR THE OUTPUT REGULATION OF SPROTT-H SYSTEM
ADAPTIVE STABILIZATION AND SYNCHRONIZATION OF HYPERCHAOTIC QI SYSTEM
ADAPTIVE CONTROLLER DESIGN FOR THE ANTI-SYNCHRONIZATION OF HYPERCHAOTIC YANG ...
Modified Projective Synchronization of Chaotic Systems with Noise Disturbance,...
ADAPTIVE CONTROL AND SYNCHRONIZATION OF HYPERCHAOTIC NEWTON-LEIPNIK SYSTEM
OUTPUT REGULATION OF SHIMIZU-MORIOKA CHAOTIC SYSTEM BY STATE FEEDBACK CONTROL
STABILITY ANALYSIS AND CONTROL OF A 3-D AUTONOMOUS AI-YUAN-ZHI-HAO HYPERCHAOT...
An Exponential Observer Design for a Class of Chaotic Systems with Exponentia...
HYBRID SLIDING SYNCHRONIZER DESIGN OF IDENTICAL HYPERCHAOTIC XU SYSTEMS
40220140501006
Ad

Similar to ANTI-SYNCHRONIZATION OF HYPERCHAOTIC BAO AND HYPERCHAOTIC XU SYSTEMS VIA ACTIVE CONTROL (20)

PDF
International Journal of Information Technology Convergence and services (IJI...
PDF
ACTIVE CONTROLLER DESIGN FOR GLOBAL CHAOS SYNCHRONIZATION OF HYPERCHAOTIC BAO...
PDF
Active Controller Design For Global Chaos Synchronization Of Hyperchaotic Bao...
PDF
HYBRID CHAOS SYNCHRONIZATION OF HYPERCHAOTIC LIU AND HYPERCHAOTIC CHEN SYSTEM...
PDF
ANTI-SYNCHRONIZATION OF HYPERCHAOTIC PANG AND HYPERCHAOTIC WANG-CHEN SYSTEMS ...
PDF
International Journal of Computer Science, Engineering and Information Techno...
PDF
SYNCHRONIZATION OF A FOUR-WING HYPERCHAOTIC SYSTEM
PDF
SYNCHRONIZATION OF A FOUR-WING HYPERCHAOTIC SYSTEM
PDF
SYNCHRONIZATION OF A FOUR-WING HYPERCHAOTIC SYSTEM
PDF
International Journal of Instrumentation and Control Systems (IJICS)
PDF
Anti-Synchronization Of Four-Scroll Chaotic Systems Via Sliding Mode Control
PDF
The International Journal of Information Technology, Control and Automation (...
PDF
GLOBAL CHAOS SYNCHRONIZATION OF HYPERCHAOTIC QI AND HYPERCHAOTIC JHA SYSTEMS ...
PDF
Global Chaos Synchronization of Hyperchaotic Pang and Hyperchaotic Wang Syste...
PDF
Adaptive Control and Synchronization of Hyperchaotic Cai System
PDF
DYNAMICS, ADAPTIVE CONTROL AND EXTENDED SYNCHRONIZATION OF HYPERCHAOTIC SYSTE...
PDF
ADAPTIVE CONTROLLER DESIGN FOR THE HYBRID SYNCHRONIZATION OF HYPERCHAOTIC XU ...
PDF
DYNAMICS, ADAPTIVE CONTROL AND EXTENDED SYNCHRONIZATION OF HYPERCHAOTIC SYSTE...
PDF
DYNAMICS, ADAPTIVE CONTROL AND EXTENDED SYNCHRONIZATION OF HYPERCHAOTIC SYSTE...
PDF
ADAPTIVE CONTROL AND SYNCHRONIZATION OF A HIGHLY CHAOTIC ATTRACTOR
International Journal of Information Technology Convergence and services (IJI...
ACTIVE CONTROLLER DESIGN FOR GLOBAL CHAOS SYNCHRONIZATION OF HYPERCHAOTIC BAO...
Active Controller Design For Global Chaos Synchronization Of Hyperchaotic Bao...
HYBRID CHAOS SYNCHRONIZATION OF HYPERCHAOTIC LIU AND HYPERCHAOTIC CHEN SYSTEM...
ANTI-SYNCHRONIZATION OF HYPERCHAOTIC PANG AND HYPERCHAOTIC WANG-CHEN SYSTEMS ...
International Journal of Computer Science, Engineering and Information Techno...
SYNCHRONIZATION OF A FOUR-WING HYPERCHAOTIC SYSTEM
SYNCHRONIZATION OF A FOUR-WING HYPERCHAOTIC SYSTEM
SYNCHRONIZATION OF A FOUR-WING HYPERCHAOTIC SYSTEM
International Journal of Instrumentation and Control Systems (IJICS)
Anti-Synchronization Of Four-Scroll Chaotic Systems Via Sliding Mode Control
The International Journal of Information Technology, Control and Automation (...
GLOBAL CHAOS SYNCHRONIZATION OF HYPERCHAOTIC QI AND HYPERCHAOTIC JHA SYSTEMS ...
Global Chaos Synchronization of Hyperchaotic Pang and Hyperchaotic Wang Syste...
Adaptive Control and Synchronization of Hyperchaotic Cai System
DYNAMICS, ADAPTIVE CONTROL AND EXTENDED SYNCHRONIZATION OF HYPERCHAOTIC SYSTE...
ADAPTIVE CONTROLLER DESIGN FOR THE HYBRID SYNCHRONIZATION OF HYPERCHAOTIC XU ...
DYNAMICS, ADAPTIVE CONTROL AND EXTENDED SYNCHRONIZATION OF HYPERCHAOTIC SYSTE...
DYNAMICS, ADAPTIVE CONTROL AND EXTENDED SYNCHRONIZATION OF HYPERCHAOTIC SYSTE...
ADAPTIVE CONTROL AND SYNCHRONIZATION OF A HIGHLY CHAOTIC ATTRACTOR
Ad

More from IJCSEIT Journal (20)

PDF
ANALYSIS OF EXISTING TRAILERS’ CONTAINER LOCK SYSTEMS
PDF
A MODEL FOR REMOTE ACCESS AND PROTECTION OF SMARTPHONES USING SHORT MESSAGE S...
PDF
BIOMETRIC APPLICATION OF INTELLIGENT AGENTS IN FAKE DOCUMENT DETECTION OF JOB...
PDF
FACE RECOGNITION USING DIFFERENT LOCAL FEATURES WITH DIFFERENT DISTANCE TECHN...
PDF
BIOMETRICS AUTHENTICATION TECHNIQUE FOR INTRUSION DETECTION SYSTEMS USING FIN...
PDF
PERFORMANCE ANALYSIS OF FINGERPRINTING EXTRACTION ALGORITHM IN VIDEO COPY DET...
PDF
Effect of Interleaved FEC Code on Wavelet Based MC-CDMA System with Alamouti ...
PDF
FUZZY WEIGHTED ASSOCIATIVE CLASSIFIER: A PREDICTIVE TECHNIQUE FOR HEALTH CARE...
PDF
GENDER RECOGNITION SYSTEM USING SPEECH SIGNAL
PDF
DETECTION OF CONCEALED WEAPONS IN X-RAY IMAGES USING FUZZY K-NN
PDF
META-HEURISTICS BASED ARF OPTIMIZATION FOR IMAGE RETRIEVAL
PDF
ERROR PERFORMANCE ANALYSIS USING COOPERATIVE CONTENTION-BASED ROUTING IN WIRE...
PDF
M-FISH KARYOTYPING - A NEW APPROACH BASED ON WATERSHED TRANSFORM
PDF
RANDOMIZED STEGANOGRAPHY IN SKIN TONE IMAGES
PDF
A NOVEL WINDOW FUNCTION YIELDING SUPPRESSED MAINLOBE WIDTH AND MINIMUM SIDELO...
PDF
CSHURI – Modified HURI algorithm for Customer Segmentation and Transaction Pr...
PDF
AN EFFICIENT IMPLEMENTATION OF TRACKING USING KALMAN FILTER FOR UNDERWATER RO...
PDF
USING DATA MINING TECHNIQUES FOR DIAGNOSIS AND PROGNOSIS OF CANCER DISEASE
PDF
FACTORS AFFECTING ACCEPTANCE OF WEB-BASED TRAINING SYSTEM: USING EXTENDED UTA...
PDF
PROBABILISTIC INTERPRETATION OF COMPLEX FUZZY SET
ANALYSIS OF EXISTING TRAILERS’ CONTAINER LOCK SYSTEMS
A MODEL FOR REMOTE ACCESS AND PROTECTION OF SMARTPHONES USING SHORT MESSAGE S...
BIOMETRIC APPLICATION OF INTELLIGENT AGENTS IN FAKE DOCUMENT DETECTION OF JOB...
FACE RECOGNITION USING DIFFERENT LOCAL FEATURES WITH DIFFERENT DISTANCE TECHN...
BIOMETRICS AUTHENTICATION TECHNIQUE FOR INTRUSION DETECTION SYSTEMS USING FIN...
PERFORMANCE ANALYSIS OF FINGERPRINTING EXTRACTION ALGORITHM IN VIDEO COPY DET...
Effect of Interleaved FEC Code on Wavelet Based MC-CDMA System with Alamouti ...
FUZZY WEIGHTED ASSOCIATIVE CLASSIFIER: A PREDICTIVE TECHNIQUE FOR HEALTH CARE...
GENDER RECOGNITION SYSTEM USING SPEECH SIGNAL
DETECTION OF CONCEALED WEAPONS IN X-RAY IMAGES USING FUZZY K-NN
META-HEURISTICS BASED ARF OPTIMIZATION FOR IMAGE RETRIEVAL
ERROR PERFORMANCE ANALYSIS USING COOPERATIVE CONTENTION-BASED ROUTING IN WIRE...
M-FISH KARYOTYPING - A NEW APPROACH BASED ON WATERSHED TRANSFORM
RANDOMIZED STEGANOGRAPHY IN SKIN TONE IMAGES
A NOVEL WINDOW FUNCTION YIELDING SUPPRESSED MAINLOBE WIDTH AND MINIMUM SIDELO...
CSHURI – Modified HURI algorithm for Customer Segmentation and Transaction Pr...
AN EFFICIENT IMPLEMENTATION OF TRACKING USING KALMAN FILTER FOR UNDERWATER RO...
USING DATA MINING TECHNIQUES FOR DIAGNOSIS AND PROGNOSIS OF CANCER DISEASE
FACTORS AFFECTING ACCEPTANCE OF WEB-BASED TRAINING SYSTEM: USING EXTENDED UTA...
PROBABILISTIC INTERPRETATION OF COMPLEX FUZZY SET

Recently uploaded (20)

PDF
keyrequirementskkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk
DOCX
ASol_English-Language-Literature-Set-1-27-02-2023-converted.docx
PPTX
Geodesy 1.pptx...............................................
PDF
R24 SURVEYING LAB MANUAL for civil enggi
PPTX
FINAL REVIEW FOR COPD DIANOSIS FOR PULMONARY DISEASE.pptx
PPTX
Recipes for Real Time Voice AI WebRTC, SLMs and Open Source Software.pptx
PPT
CRASH COURSE IN ALTERNATIVE PLUMBING CLASS
PDF
July 2025 - Top 10 Read Articles in International Journal of Software Enginee...
PPT
Project quality management in manufacturing
PDF
Mohammad Mahdi Farshadian CV - Prospective PhD Student 2026
PPTX
OOP with Java - Java Introduction (Basics)
PDF
Automation-in-Manufacturing-Chapter-Introduction.pdf
PPTX
Foundation to blockchain - A guide to Blockchain Tech
PDF
Mitigating Risks through Effective Management for Enhancing Organizational Pe...
PDF
PRIZ Academy - 9 Windows Thinking Where to Invest Today to Win Tomorrow.pdf
PPTX
bas. eng. economics group 4 presentation 1.pptx
PDF
Embodied AI: Ushering in the Next Era of Intelligent Systems
PPTX
CH1 Production IntroductoryConcepts.pptx
PDF
Digital Logic Computer Design lecture notes
PPTX
MCN 401 KTU-2019-PPE KITS-MODULE 2.pptx
keyrequirementskkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk
ASol_English-Language-Literature-Set-1-27-02-2023-converted.docx
Geodesy 1.pptx...............................................
R24 SURVEYING LAB MANUAL for civil enggi
FINAL REVIEW FOR COPD DIANOSIS FOR PULMONARY DISEASE.pptx
Recipes for Real Time Voice AI WebRTC, SLMs and Open Source Software.pptx
CRASH COURSE IN ALTERNATIVE PLUMBING CLASS
July 2025 - Top 10 Read Articles in International Journal of Software Enginee...
Project quality management in manufacturing
Mohammad Mahdi Farshadian CV - Prospective PhD Student 2026
OOP with Java - Java Introduction (Basics)
Automation-in-Manufacturing-Chapter-Introduction.pdf
Foundation to blockchain - A guide to Blockchain Tech
Mitigating Risks through Effective Management for Enhancing Organizational Pe...
PRIZ Academy - 9 Windows Thinking Where to Invest Today to Win Tomorrow.pdf
bas. eng. economics group 4 presentation 1.pptx
Embodied AI: Ushering in the Next Era of Intelligent Systems
CH1 Production IntroductoryConcepts.pptx
Digital Logic Computer Design lecture notes
MCN 401 KTU-2019-PPE KITS-MODULE 2.pptx

ANTI-SYNCHRONIZATION OF HYPERCHAOTIC BAO AND HYPERCHAOTIC XU SYSTEMS VIA ACTIVE CONTROL

  • 1. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012 DOI : 10.5121/ijcseit.2012.2306 81 ANTI-SYNCHRONIZATION OF HYPERCHAOTIC BAO AND HYPERCHAOTIC XU SYSTEMS VIA ACTIVE CONTROL Sundarapandian Vaidyanathan 1 Research and Development Centre, Vel Tech Dr. RR & Dr. SR Technical University Avadi, Chennai-600 062, Tamil Nadu, INDIA sundarvtu@gmail.com Abstract This paper investigates the anti-synchronization of identical hyperchaotic Bao systems (Bao and Liu, 2008), identical hyperchaotic Xu systems (Xu, Cai and Zheng, 2009) and non-identical hyperchaotic Bao and hyperchaotic Xu systems. Active nonlinear control has been deployed for the anti- synchronization of the hyperchaotic systems addressed in this paper and the main results have been established using Lyapunov stability theory. Since the Lyapunov exponents are not required for these calculations, the active nonlinear control method is very effective and convenient to achieve anti-synchronization of identical and non-identical hyperchaotic Bao and hyperchaotic Xu systems. Numerical simulations have been provided to validate and demonstrate the effectiveness of the anti-synchronization results for the hyperchaotic Cao and hyperchaotic Xu systems. KEYWORDS Active Control, Anti-Synchronization, Hyperchaos, Hyperchaotic Bao System, Hyperchaotic Xu System. 1. INTRODUCTION Chaos is a complex nonlinear phenomenon. The first chaotic attractor was discovered by Lorenz ([1], 1963), when he was studying the atmospheric convection in the weather models. Since then, chaos has been received extensive investigations and chaos phenomenon has been observed in a variety of fields including physical systems [2], chemical systems [3], ecological systems [4], secure communications [5-6], etc. The seminal work on chaos synchronization problem was published by Pecora and Carroll ([7], 1990). From then on, chaos synchronization has been extensively and intensively studied in the last three decades [8-30]. In most of the anti-synchronization approaches, the master-slave or drive-response formalism is used. If a particular chaotic system is called the master or drive system and another chaotic system is called the slave or response system, then the idea of anti-synchronization is to use the output of the master system to control the slave system so that the states of the slave system have the same amplitude but opposite signs as the states of the master system asymptotically. Thus, when anti-synchronization is achieved, the sum of the states of the master and slave systems tends to zero asymptotically with time.
  • 2. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012 82 In the recent years, various schemes have been deployed for chaos synchronization such as PC method [2], OGY method [8], active control [9-12], adaptive control [13-15], backstepping design [16], sampled-data feedback [17], sliding mode control [18-20], etc. Recently, active control method has been applied to achieve anti-synchronization of two identical chaotic systems [21-22]. Hyperchaotic system is usually defined as a chaotic system with at least two positive Lyapunov exponents, implying that its dynamics are expanded in several different directions simultaneously. Thus, the hyperchaotic systems have more complex dynamical behaviour which can be used to improve the security of a chaotic communication system. Hence, the theoretical design and circuit realization of various hyperchaotic signals have become important research topics [23-27]. In this paper, we use active control to derive new results for the anti-synchronization of identical hyperchaotic Bao systems ([28], 2008), identical hyperchaotic Xu systems ([29], 2009) and non- identical hyperchaotic Bao and hyperchaotic Xu systems. This paper is organized as follows. In Section 2, we describe the problem statement and our methodology using Lyapunov stability theory. In Section 3, we provide a description of the hyperchaotic systems addressed in this paper. In Section 4, we discuss the anti-synchronization of identical hyperchaotic Bao systems (2008) using active nonlinear control. In Section 5, we discuss the anti-synchronization of identical hyperchaotic Xu systems (2009) using active nonlinear control. In Section 6, we discuss the anti-synchronization of hyperchaotic Bao and hyperchaotic Xu systems using active nonlinear control. In Section 7, we summarize the main results obtained in this paper. 2. PROBLEM STATEMENT AND OUR METHODOLOGY As the master or drive system, we consider the chaotic system described by ( ),x Ax f x= +& (1) where n x∈R is the state vector, A is the n n× matrix of system parameters and : n n f →R R is the nonlinear part of the system. As the slave or response system, we consider the following chaotic system described by ( ) ,y By g y u= + +& (2) where n y ∈R is the state of the slave system, B is the n n× matrix of system parameters, : n n g →R R is the nonlinear part of the system and u is the active controller to be designed. If A B= and ,f g= then x and y are the states of two identical chaotic systems. If A B≠ or ,f g≠ then x and y are the states of two different chaotic systems. For the anti-synchronization of the chaotic systems (1) and (2) using active control, we design a state feedback controller ,u which anti-synchronizes the states of the master system (1) and the slave system (2) for all initial conditions (0), (0) .n x y ∈R Thus, we define the anti-synchronization error as
  • 3. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012 83 ,e y x= + (3) Hence, the error dynamics is obtained as ( ) ( )e By Ax g y f x u= + + + +& (4) Thus, the anti-synchronization problem is essentially to find a feedback controller (active controller) u so as to stabilize the error dynamics (4) for all initial conditions, i.e. lim ( ) 0, t e t →∞ = for all (0) n e ∈R (5) We use the Lyapunov stability theory as our methodology. We take as a candidate Lyapunov function ( ) ,T V e e Pe= (6) where P is a positive definite matrix. Note that : n V R→R is a positive definite function by construction. If we find a feedback controller u so that ( ) ,T V e e Qe= −& (7) where Q is a positive definite matrix, then : n V →& R R is a negative definite function. Thus, by Lyapunov stability theory [25], the error dynamics (4) is globally exponentially stable. Hence, the states of the master system (1) and the slave system (2) will be globally and exponentially anti-synchronized for all values of the initial conditions (0), (0) .n x y ∈R 3. SYSTEMS DESCRIPTION The hyperchaotic Bao system ([28], 2008) is described by the 4D dynamics 1 2 1 4 2 2 1 3 3 1 2 3 4 1 2 3 ( )x a x x x x cx x x x x x bx x x dx xε = − + = − = − = + & & & & (8) where 1 2 3 4, , ,x x x x are the state variables and , , , ,a b c d ε are positive constants. The four-dimensional Bao system (8) is hyperchaotic when 36, 3, 20, 0.1a b c d= = = = and 21.ε =
  • 4. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012 84 The phase portrait of the hyperchaotic Bao system is shown in Figure 1. Figure 1. Phase Portrait of the Hyperchaotic Bao System The hyperchaotic Xu system ([29], 2009) is described by the 4D dynamics 1 2 1 4 2 1 1 3 3 3 1 2 4 1 3 2 ( )x x x x x x rx x x x lx x x x x mx α β γ = − + = + = − − = − & & & & (9) where 1 2 3 4, , ,x x x x are the state variables and , , , ,l mα β γ are positive constants. The four-dimensional Xu system (9) is hyperchaotic when 10, 40, 2.5, 16, 1r lα β γ= = = = = and 2.m = The phase portrait of the hyperchaotic Xu system is shown in Figure 2.
  • 5. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012 85 Figure 2. Phase Portrait of the Hyperchaotic Xu System 3. ANTI-SYNCHRONIZATION OF HYPERCHAOTIC BAO SYSTEMS In this section, we discuss the anti-synchronization of identical hyperchaotic Bao systems ([28], 2008). As the master system, we consider the hyperchaotic Bao system described by 1 2 1 4 2 2 1 3 3 1 2 3 4 1 2 3 ( )x a x x x x cx x x x x x bx x x dx xε = − + = − = − = + & & & & (10) where 1 2 3 4, , ,x x x x are the state variables and , , , ,a b c d ε are positive constants. As the slave system, we consider the controlled hyperchaotic Bao dynamics described by 1 2 1 4 1 2 2 1 3 2 3 1 2 3 3 4 1 2 3 4 ( )y a y y y u y cy y y u y y y by u y y dy y uε = − + + = − + = − + = + + & & & & (11) where 1 2 3 4, , ,y y y y are the state variables and 1 2 3 4, , ,u u u u are the active controls.
  • 6. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012 86 The anti-synchronization error is defined as 1 1 1 2 2 2 3 3 3 4 4 4 e y x e y x e y x e y x = + = + = + = + (12) A simple calculation gives the error dynamics 1 2 1 4 1 2 2 1 3 1 3 2 3 3 1 2 1 2 3 4 1 2 3 2 3 4 ( ) ( ) e a e e e u e ce y y x x u e be y y x x u e e d y y x x uε = − + + = − − + = − + + + = + + + & & & & (13) We consider the active nonlinear controller defined by 1 2 1 4 1 1 2 2 1 3 1 3 2 2 3 3 1 2 1 2 3 3 4 1 2 3 2 3 4 4 ( ) ( ) u a e e e k e u ce y y x x k e u be y y x x k e u e d y y x x k eε = − − − − = − + + − = − − − = − − + − (14) where 1 2 3 4, , ,k k k k are positive constants. Substitution of (14) into (13) yields the linear error dynamics 1 1 1 2 2 2 3 3 3 4 4 4, , ,e k e e k e e k e e k e= − = − = − = −& & & & (15) We consider the quadratic Lyapunov function defined by ( )2 2 2 2 1 2 3 4 1 1 ( ) , 2 2 T V e e e e e e e= = + + + (16) which is a positive definite function on 4 .R Next, we establish the main result of this section using Lyapunov stability theory. Theorem 1. The identical hyperchaotic Bao systems (10) and (11) are globally and exponentially anti-synchronized with the active nonlinear controller (13). Proof. Differentiating (16) along the trajectories of the error system (15), we get 2 2 2 2 1 1 2 2 3 3 4 4( ) ,V e k e k e k e k e= − − − −& (17) which is a negative definite function on 4 R
  • 7. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012 87 Thus, by Lyapunov stability theory [30], the error dynamics (15) is globally exponentially stable. This completes the proof. Numerical Simulations: For the numerical simulations, the fourth order Runge-Kutta method with initial time-step 8 10h − = is used to solve the two systems of differential equations (10) and (11) with the active nonlinear controller (14). We take the gains as 5ik = for 1,2,3,4.i = The parameters of the identical hyperchaotic Bao systems (8) and (9) are selected as 36, 3, 20, 0.1a b c d= = = = and 21.ε = The initial values for the master system (8) are taken as 1 2 3 4(0) 5, (0) 2, (0) 14, (0) 20x x x x= = − = = and the initial values for the slave system (9) are taken as 1 2 3 4(0) 24, (0) 17, (0) 18, (0) 22y y y y= = = − = − Figure 4 depicts the anti-synchronization of the identical hyperchaotic Bao systems (10) and (11). Figure 4 depicts the time-history of the anti-synchronization error. Figure 3. Anti-Synchronization of Identical Hyperchaotic Bao Systems
  • 8. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012 88 Figure 4. Time-History of Anti-Synchronization Error 1 2 3 4, , ,e e e e 4. ANTI-SYNCHRONIZATION OF HYPERCHAOTIC XU SYSTEMS In this section, we discuss the anti-synchronization of identical hyperchaotic Xu systems ([29], 2009). As the master system, we consider the hyperchaotic Xu system described by 1 2 1 4 2 1 1 3 3 3 1 2 4 1 3 2 ( )x x x x x x rx x x x lx x x x x mx α β γ = − + = + = − − = − & & & & (18) where 1 2 3 4, , ,x x x x are the state variables and , , , , ,r l mα β γ are positive constants. As the slave system, we consider the controlled hyperchaotic Xu dynamics described by 1 2 1 4 1 2 1 1 3 2 3 3 1 2 3 4 1 3 2 4 ( )y y y y u y y ry y u y y ly y u y y y my u α β γ = − + + = + + = − − + = − + (19)
  • 9. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012 89 where 1 2 3 4, , ,y y y y are the state variables and 1 2 3 4, , ,u u u u are the active controls. The anti-synchronization error is defined as 1 1 1 2 2 2 3 3 3 4 4 4 e y x e y x e y x e y x = + = + = + = + (20) A simple calculation gives the error dynamics 1 2 1 4 1 2 1 1 3 1 3 2 3 3 1 2 1 2 3 4 2 1 3 1 3 4 ( ) ( ) ( ) e e e e u e e r y y x x u e e l y y x x u e me y y x x u α β γ = − + + = + + + = − − + + = − + + + & & & & (21) We consider the active nonlinear controller defined by 1 2 1 4 1 1 2 1 1 3 1 3 2 2 3 3 1 2 1 2 3 3 4 2 1 3 1 3 4 4 ( ) ( ) ( ) u e e e k e u e r y y x x k e u e l y y x x k e u me y y x x k e α β γ = − − − − = − − + − = + + − = − − − (22) where 1 2 3 4, , ,k k k k are positive constants. Substitution of (22) into (21) yields the linear error dynamics 1 1 1 2 2 2 3 3 3 4 4 4, , ,e k e e k e e k e e k e= − = − = − = −& & & & (23) We consider the quadratic Lyapunov function defined by ( )2 2 2 2 1 2 3 4 1 1 ( ) , 2 2 T V e e e e e e e= = + + + (24) which is a positive definite function on 4 .R Next, we establish the main result of this section using Lyapunov stability theory. Theorem 2. The identical hyperchaotic Xu systems (18) and (19) are globally and exponentially anti-synchronized with the active nonlinear controller (22). Proof. Differentiating (16) along the trajectories of the error system (15), we get
  • 10. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012 90 2 2 2 2 1 1 2 2 3 3 4 4( ) ,V e k e k e k e k e= − − − −& (25) which is a negative definite function on 4 R Thus, by Lyapunov stability theory [30], the error dynamics (23) is globally exponentially stable. Hence, the states of the identical hyperchaotic Xu systems (18) and (19) are globally and exponentially anti-synchronized for all initial conditions (0), (0) .n x y ∈R This completes the proof. Numerical Simulations: For the numerical simulations, the fourth order Runge-Kutta method with initial time-step 6 10h − = is used to solve the two systems of differential equations (18) and (19) with the active nonlinear controller (22). We take the feedback gains as 1 2 3 45, 5, 5, 5k k k k= = = = The parameters of the identical hyperchaotic Xu systems (18) and (19) are selected as 10, 40, 2.5, 16, 1r lα β γ= = = = = and 2.m = The initial values for the master system (18) are taken as 1 2 3 4(0) 12, (0) 14, (0) 7, (0) 21x x x x= = − = − = and the initial values for the slave system (19) are taken as 1 2 3 4(0) 26, (0) 10, (0) 18, (0) 4y y y y= = = = − Figure 5 depicts the anti-synchronization of the identical hyperchaotic Xu systems (18) and (19). Figure 6 depicts the time-history of the anti-synchronisation error 1 2 3 4, , , .e e e e
  • 11. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012 91 Figure 5. Anti-Synchronization of Identical Hyperchaotic Xu Systems Figure 6. Time-History of the Anti-Synchronization Error 1 2 3 4, , ,e e e e
  • 12. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012 92 5. ANTI-SYNCHRONIZATION OF HYPERCHAOTIC BAO AND HYPERCHAOTIC XU SYSTEMS In this section, we consider the anti-synchronization of non-identical hyperchaotic Bao system ([28], 2008) and hyperchaotic Xu system ([29], 2009). As the master system, we consider the hyperchaotic Bao system described by 1 2 1 4 2 2 1 3 3 1 2 3 4 1 2 3 ( )x a x x x x cx x x x x x bx x x dx xε = − + = − = − = + & & & & (26) where 1 2 3 4, , ,x x x x are the state variables and , , , ,a b c d ε are positive constants. As the slave system, we consider the controlled hyperchaotic Xu dynamics described by 1 2 1 4 1 2 1 1 3 2 3 3 1 2 3 4 1 3 2 4 ( )y y y y u y y ry y u y y ly y u y y y my u α β γ = − + + = + + = − − + = − + (27) where 1 2 3 4, , ,y y y y are the state variables, , , , , ,r l mα β γ are positive constants and 1 2 3 4, , ,u u u u are the active controls. The anti-synchronization error is defined as 1 1 1 2 2 2 3 3 3 4 4 4 e y x e y x e y x e y x = + = + = + = + (28) A simple calculation gives the error dynamics 1 2 1 4 2 1 1 2 1 1 2 1 3 1 3 2 3 3 3 1 2 1 2 3 4 2 1 2 1 3 2 3 4 ( ) ( )( ) ( ) e e e e a x x u e e x cx ry y x x u e e b x ly y x x u e me x mx y y dx x u α α β β γ γ ε = − + − − − + = − + + − + = − − − − + + = − + + + + + & & & & (29)
  • 13. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012 93 We consider the active nonlinear controller defined by 1 2 1 4 2 1 1 1 2 1 1 2 1 3 1 3 2 2 3 3 3 1 2 1 2 3 3 4 2 1 2 1 3 2 3 4 4 ( ) ( )( ) ( ) u e e e a x x k e u e x cx ry y x x k e u e b x ly y x x k e u me x mx y y dx x k e α α β β γ γ ε = − − − + − − − = − + − − + − = + − + − − = − − − − − (30) Substitution of (30) into (29) yields the linear error dynamics 1 1 1 2 2 2 3 3 3 4 4 4 e k e e k e e k e e k e = − = − = − = − & & & & (31) We consider the quadratic Lyapunov function defined by ( )2 2 2 2 1 2 3 4 1 1 ( ) , 2 2 T V e e e e e e e= = + + + (32) which is a positive definite function on 4 .R Next, we establish the main result of this section using Lyapunov stability theory. Theorem 3. The non-identical hyperchaotic Bao system (26) and hyperchaotic Xu system (27) are globally and exponentially anti-synchronized with the active nonlinear controller (29). Proof. Differentiating (32) along the trajectories of the error system (31), we get 2 2 2 2 1 1 2 2 3 3 4 4( ) ,V e k e k e k e k e= − − − −& (33) which is a negative definite function on 4 R since α and γ are positive constants. Thus, by Lyapunov stability theory [30], the error dynamics (31) is globally exponentially stable. Hence, it follows that the states of the hyperchaotic Bao system (26) and hyperchaotic Xu system (27) are globally and exponentially anti-synchronized for all initial conditions (0), (0) .n x y ∈R This completes the proof.
  • 14. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012 94 Numerical Simulations For the numerical simulations, the fourth order Runge-Kutta method with initial time-step 6 10h − = is used to solve the two systems of differential equations (26) and (27) with the active nonlinear controller (30). We take the feedback gains as 1 2 35, 5, 5k k k= = = and 4 5.k = The parameters of the identical hyperchaotic Bao system (24) are selected as 36, 3, 20, 0.1a b c d= = = = and 21.ε = The parameters of the identical hyperchaotic Xu system (25) are selected as 10, 40, 2.5, 16, 1r lα β γ= = = = = and 2.m = The initial values for the master system (26) are taken as 1 2 3 4(0) 25, (0) 6, (0) 9, (0) 14x x x x= = − = = − and the initial values for the slave system (27) are taken as 1 2 3 4(0) 12, (0) 15, (0) 20, (0) 8y y y y= = = − = − Figure 7 depicts the anti-synchronization of the non-identical hyperchaotic systems, viz. hyperchaotic Bao system (26) and hyperchaotic Xu system (28). Figure 8 depicts the time-history of the anti-synchronization error. 6. CONCLUSIONS In this paper, using the active control method, new results have been derived for the anti- synchronization for the following pairs of hyperchaotic systems: (A) Identical hyperchaotic Bao systems (2008) (B) Identical hyperchaotic Xu systems (2009) (C) Non-identical hyperchaotic Bao and hyperchaotic Xu systems. The anti-synchronization results derived in this paper have been proved using Lyapunov stability theory. Since the Lyapunov exponents are not required for these calculations, the active control method is very convenient and efficient for the anti- synchronization of identical and non- identical hyperchaotic Bao and hyperchaotic Xu systems. Numerical simulation results have been presented to illustrate the anti-synchronization results derived in this paper.
  • 15. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012 95 Figure 7. Anti-Synchronization of Hyperchaotic Bao and Hyperchaotic Xu Systems Figure 8. Time-History of the Anti-Synchronization Error 1 2 3 4, , ,e e e e
  • 16. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012 96 REFERENCES [1] Lorenz, E.N. (1963) “Deterministic nonperiodic flow”, J. Atmos. Sci., Vol. 20, pp 130-141. [2] Lakshmanan, M. & Murali, K. (1996) Nonlinear Oscillators: Controlling and Synchronization, World Scientific, Singapore. [3] Han, S.K., Kerrer, C. & Kuramoto, Y. (1995) “Dephasing and burstling in coupled neural oscillators”, Phys. Rev. Lett., Vol. 75, pp 3190-3193. [4] Blasius, B., Huppert, A. & Stone, L. (1999) “Complex dynamics and phase synchronization in spatially extended ecological system”, Nature, Vol. 399, pp 354-359. [5] Feki, M. (2003) “An adaptive chaos synchronization scheme applied to secure communication”, Chaos, Solitons and Fractals, Vol. 18, pp 141-148. [6] Murali, K. & Lakshmanan, M. (1998) “Secure communication using a compound signal from generalized synchronizable chaotic systems”, Phys. Rev. Lett. A, Vol. 241, pp 303-310. [7] Pecora, L.M. & Carroll, T.L. (1990) “Synchronization in chaotic systems”, Phys. Rev. Lett., Vol. 64, pp 821-824. [8] Ott, E., Grebogi, C. & Yorke, J.A. (1990) “Controlling chaos”, Phys. Rev. Lett., Vol. 64, pp 1196- 1199. [9] Ho, M.C. & Hung, Y.C. (2002) “Synchronization of two different chaotic systems by using generalized active control”, Physics Letters A, Vol. 301, pp. 424-428. [10] Chen, H.K. (2005) “Global chaos synchronization of new chaotic systems via nonlinear control”, Chaos, Solitons & Fractals, Vol. 23, pp. 1245-1251. [11] Sundarapandian, V. (2011) “Global chaos synchronization of four-scroll and four-wing chaotic attractors by active nonlinear control,” International Journal on Computer Science and Engineering, Vol. 3, No. 5, pp. 2145-2155. [12] Sundarapandian, V. (2011) “Anti-synchronization of Arneodo and Coullet systems by active nonlinear control,” International Journal of Control Theory and Applications, Vol. 4, No. 1, pp. 25- 36. [13] Liao, T.L. & Tsai, S.H. (2000) “Adaptive synchronization of chaotic systems and its applications to secure communications”, Chaos, Solitons and Fractals, Vol. 11, pp 1387-1396. [14] Sundarapandian, V. (2011) “Adaptive control and synchronization of hyperchaotic Cai system”, International Journal of Control Theory and Computer Modelling, Vol. 1, No. 1, pp. 1-13. [15] Sundarapandian, V. (2011) “Adaptive synchronization of hyperchaotic Lorenz and hyperchaotic Liu systems”, International Journal of Instrumentation and Control Systems, Vol. 1, No. 1, pp. 1-18. [16] Yu, Y.G. & Zhang, S.C. (2006) “Adaptive backstepping synchronization of uncertain chaotic systems”, Chaos, Solitons and Fractals, Vol. 27, pp 1369-1375. [17] Yang, T. & Chua, L.O. (1999) “Control of chaos using sampled-data feedback control”, Internat. J. Bifurcat. Chaos, Vol. 9, pp 215-219. [18] Sundarapandian, V. (2011) “Global chaos synchronization of four-wing chaotic systems by sliding mode control”, International Journal of Control Theory and Computer Modelling, Vol. 1, No. 1, pp. 15-31. [19] Sundarapandian, V. (2011) “Global chaos synchronization of Pehlivan systems by sliding mode control”, International Journal on Computer Science and Engineering, Vol. 3, No. 5, pp. 2163-2169. [20] Sundarapandian, V. (2011) “Sliding mode controller design for the synchronization of Shimizu- Morioka chaotic systems”, International Journal of Information Sciences and Techniques, Vol. 1, No. 1, pp 20-29. [21] Li, G.H. (2005) “Synchronization and anti-synchronization of Colpitts oscillators using active control,” Chaos, Solitons & Fractals, Vol. 26, pp 87-93. [22] Hu, J. (2005) “Adaptive control for anti-synchronization of Chua’s chaotic system”, Physics Letters A, Vol. 339, pp. 455-460. [23] Rössler, O.E. (1979) “An equation for hyperchaos”, Phys. Letters A, Vol. 71, pp 155-157. [24] Thamilmaran, K., Lakshmanan, M. & Venkatesan, A. (2004) “A hyperchaos in a modified canonical Chua’s circuit”, International J. Bifurcat. Chaos, Vol. 14, pp 221-243. [25] Vicente, R., Dauden, J., Colet, P. & Toral, R. (2005) “Analysis and characterization of the hyperchaos generated by a semiconductor laser object”, IEEE J. Quantum Electronics, Vol. 41, pp 541-548. [26] Li, Y., Tang, W.K.S. & Chen, G. (2005) “Generating hyperchaos via state feedback control,” Internat. J. Bifurcat. Chaos, Vol. 15, No. 10, pp 3367-3375.
  • 17. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.3, June 2012 97 [27] Wang, J. & Chen, J. (2008) “A novel hyperchaotic system and its complex dynamics”, Internat. J. Bifurcat. Chaos, Vol. 18, No. 11, pp 3309-3324. [28] Bao, B.C. & Liu, Z. (2008) “A hyperchaotic attractor coined from the chaotic Lü system”, Chin. Physics Letters, Vol. 25, pp 2396-2399. [29] Xu, J., Cai, G. & Zheng, S. (2009) “A novel hyperchaotic system and its control”, J. Uncertain Systems, Vol. 3, pp 137-144. [30] Hahn, W. (1967) The Stability of Motion, Springer, New York. Author Dr. V. Sundarapandian earned his Doctor of Science degree in Electrical and Systems Engineering from Washington University, Saint Louis, Missouri, USA. He is currently Professor in the Research and Development Centre at Vel Tech Dr. RR & Dr. SR Technical University, Chennai, Tamil Nadu, India. He has published over 260 publications in refereed International journals and over 170 papers in National and International Conferences. He is the Editor-in-Chief of the AIRCC journals - International Journal of Instrumentation and Control Systems, International Journal of Control Systems and Computer Modelling and International Journal of Information Technology, Control and Automation. His research interests are Linear and Nonlinear Control Systems, Chaos Theory and Control, Soft Computing, Optimal Control, Process Control, Operations Research, Mathematical Modelling, Scientific Computing using SCILAB/MATLAB. He has delivered many Keynote Lectures on Chaos Theory and Control Engineering.