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International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol. 4, No.5, October 2014 
FUNCTION PROJECTIVE SYNCHRONIZATION 
OF NEW CHAOTIC REVERSAL SYSTEMS 
Olurotimi S. Ojoniyi 
Department of Physics and Telecommunications, Tai Solarin University of Education, 
Ijagun, Ogun State Nigeria. 
ABSTRACT 
In the present work, Lyapunov stability theory, nonlinear adaptive control law and the parameter update 
law were utilized to derive the state of two new chaotic reversal systems after being synchronized by the 
function projective method. Using this technique allows for a scaling function instead of a constant thereby 
giving a better method in applications in secure communication. Numerical simulations are presented to 
demonstrate the effective nature of the proposed scheme of synchronization for the new chaotic reversal 
system. 
KEYWORDS 
Function projective synchronization, Lyapunov stability theory, chaotic system, new chaotic reversal 
system. 
1. INTRODUCTION 
The chaotic dynamics observed only in nonlinear systems have been largely defined by 
oscillations which are sensitive to initial conditions [1]. Lorenz and Rossler systems are 
pioneering simple chaotic systems discovered with a lot of interesting properties that can model 
physical systems [1]-[2]. This relatively new dynamical behaviour has since been discovered in 
other disciplines such as engineering, science and economics. In order to understand fully most 
nonlinear phenomenon in nature through interaction of systems, the control and synchronization 
of chaotic oscillations is vital. 
The process of controlling and synchronising chaotic systems has attracted much attention since 
its discovery in less than twenty years [3]. The work of Pecora and Caroll [4] generated a wider 
research in synchronization since it entails the synchronization of two identical chaotic systems 
with different initial conditions.A number of methods of synchronization have been proposed 
since the pioneering work of Pecora and Caroll such as complete synchronization, generalized 
synchronization, phase synchronization, lag synchronization, adaptive synchronization, time-scale 
synchronization, intermittent synchronization, projective synchronization and function 
projective synchronization [5]-[9]. Function projective synchronization deserves much attention 
since it has been found applicable and better in secure communication. 
Function projective synchronization implies that the master and slave oscillators could be 
synchronized up to a scaling function unlike a constant in the projective synchronization. The 
DOI : 10.5121/ijcseit.2014.4503 33
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol. 4, No.5, October 2014 
advantage is that it becomes more complex to determine the function used and as a result more 
secure communication is achieved under this scheme. 
In the present work, function projective synchronization of new chaotic reversal systems [10] 
with uncertain parameters using nonlinear adaptive controller has been investigated to 
demonstrate the effectiveness of this scheme as it applies in secure communication. The 
remaining part of this work is arranged as follows: section 2 is on the nonlinear adaptive 
controller designed to synchronize the new chaotic reversal systems, section 3 is on numerical 
simulations presented to demonstrate the robust nature of the scheme, and section 4 is the 
conclusion of the paper. 
In the present section, we examine briefly the dynamics of the new deterministic model for 
chaotic reversal [10]. 
34 
2. ADAPTIVE CONTROL SCHEME 
We have a new deterministic model for chaotic reversal by C. Gissinger [10] given by: 
 
………. (1) 
 
Where and are the states and are unknown parameters. 
The system (1) is chaotic when the parameter values are taken as: 
and as shown in figure 1. 
Strange Attractor of the New Chaotic Reversal System 
-5 
0 
5 
-5 
0 
4 
2 
0 
-2 
5 
x 
1 
3 
x 
2 x 
Figure 1: 
The system (1) is taken as master system, and the slave system with the adaptive control scheme 
is taken as 
………. (2)
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol. 4, No.5, October 2014 
Where are the parameters of the slave which needs to be estimated and are 
the nonlinear controllers such that the two new chaotic reversal systems are function projective 
synchronized in the sense that 
35 
 
……… (3) 
Where is the scaling function. 
From system (1) and (2) we get the error dynamical system which can be written as 
……… (4) 
Where 
In order to stabilize the error variables of system (3) at the origin, we propose the adaptive control 
law and the parameter update law for system (3) as follows 
…….(5) 
And the update rule for the three uncertain parameters are 
……….. (6) 
Where and 
Theorem For the given scaling function , the function projective synchronization between 
the master system (1) and the slave system (2) can be achieved if the nonlinear controller (5) and 
the update law (6) are adopted. 
Proof We construct the following Lyapunov function 
Calculating the time derivative of V along the trajectory of error system (4), we have
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol. 4, No.5, October 2014 
36 
 
… (8) 
+ 
+ 
+ [ 
Where , and . 
It is evident that is negative definite and if and only if . By the Lyapunov 
stability theory, the function projective synchronization is achieved. This ends the proof. 
3. NUMERICAL SIMULATIONS 
The numerical simulations to verify the effectiveness of the proposed function projective 
synchronization using the adaptive controllers are carried out by the fourth-order Runge-Kutta 
method. This method is used to solve the master system (1) and the slave system (2) with time 
step size . The initial conditions of the master system are 
. The scaling function is chosen as and . The figure 
2 shows that the error variables tend to zero with . Figure 3 shows that the 
estimated values of the uncertain parameters converge to as 
. 
300 
250 
200 
150 
100 
50 
0 
0 2 4 6 8 10 12 14 16 18 20 
Time / s 
e 
1
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol. 4, No.5, October 2014 
37 
 
5 
4 
3 
2 
1 
0 
-1 
0 2 4 6 8 10 12 14 16 18 20 
Time /s 
e 
2 
10 
8 
6 
4 
2 
0 
0 2 4 6 8 10 12 14 16 18 20 
Time /s 
e 
3 
Figure 2: Error dynamics between master system (1) and the slave system (2) 
100 
0 
-100 
-200 
-300 
0 2 4 6 8 10 12 14 16 18 20 
Time /s 
a 
1
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol. 4, No.5, October 2014 
38 
 
4 
3 
2 
1 
0 
-1 
0 2 4 6 8 10 12 14 16 18 20 
Time /s 
b 
1 
12 
10 
8 
6 
4 
2 
0 
0 2 4 6 8 10 12 14 16 18 20 
Time /s 
c 
1 
Figure 3: The time evolution of the estimated parameters 
4. CONCLUSION 
In the present work we have demonstrated the application of function projective synchronization 
in synchronizing the new chaotic reversal systems with uncertain parameters. The Lyapunov 
stability theory was used to design the adaptive synchronization controllers with associated 
parameter update laws to stabilize the error dynamics between the master and the slave chaotic 
oscillators. All the theoretical investigations have been verified by numerical simulations to proof 
the effectiveness of the scheme. 
REFERENCES 
[1] Lorenz, E.N. (1963) “Deterministic nonperiodic flow,” J. Atmos. Phys. Vol. 20, pp 131-141. 
[2] Rössler, O.E. (1976) “An equation for continuous chaos,” Physics Letters A, Vol. 57, pp 397-398. 
[3] Junbiao Guan, (2012 )‘’Function projective synchronization of a class of chaotic systems with 
uncertain parameters’’, Hindawi Publishing Corp., Article ID 431752, 
[4] L. M. Pecora and T. L. Carroll, (1990) “Synchronization in chaotic systems,” Physical Review 
Letters, vol. 64, no. 8, pp. 821–824,. 
[5] M. Rosenblum, A. Pikovsky, and J. Kurths, (1996) “Phase synchronization of chaotic oscillators,” 
Physical Review Letters, vol. 76, pp. 1804–1807,. 
[6] H. Taghvafard and G. H. Erjaee, (2011)“Phase and anti-phase synchronization of fractional order 
chaotic systems via active control,” Communications in Nonlinear Science and Numerical 
Simulation, vol. 16, no. 10, pp. 4079–4088,. 
[7] R. Mainieri and J. Rehacek, (1999)“Projective synchronization in three-dimensional chaotic systems,” 
Physical Review Letters, vol. 82, pp. 3042–3045,.
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol. 4, No.5, October 2014 
[8] Junbiao Guan, (2010) “Synchronization control of two different chaotic systems with known and 
39 
 
unknown parameters,” Chinese Physics Letters, vol. 27, Article ID 020502,. 
[9] L. Runzi, (2008) “Adaptive function project synchronization of Rossler hyperchaotic system with 
uncertain parameters,” Physics Letters. A, vol. 372, no. 20, pp. 3667–3671, 
[10] Gissinger, C. (2012) ‘’ A new deterministic model for chaotic reversals, ’’ Euro. Phy. J. B 85:137, pp 
1-12. 
Author 
Ojoniyi, Olurotimi Seyi is currently on a Ph.D programme in nonlinear dynamics and chaos 
at the department of Physics of the University of Agriculture, Abeokuta, Ogun State, Nigeria. 
He holds a M.Sc, degree in Physics from the University of Ibadan, Ibadan, Nigeria and is 
currently an academic Staff of Physics and Telecommunications department of Tai Solarin 
University of Education, Ijagun, Ogun State, Nigeria.

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Function projective synchronization

  • 1. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol. 4, No.5, October 2014 FUNCTION PROJECTIVE SYNCHRONIZATION OF NEW CHAOTIC REVERSAL SYSTEMS Olurotimi S. Ojoniyi Department of Physics and Telecommunications, Tai Solarin University of Education, Ijagun, Ogun State Nigeria. ABSTRACT In the present work, Lyapunov stability theory, nonlinear adaptive control law and the parameter update law were utilized to derive the state of two new chaotic reversal systems after being synchronized by the function projective method. Using this technique allows for a scaling function instead of a constant thereby giving a better method in applications in secure communication. Numerical simulations are presented to demonstrate the effective nature of the proposed scheme of synchronization for the new chaotic reversal system. KEYWORDS Function projective synchronization, Lyapunov stability theory, chaotic system, new chaotic reversal system. 1. INTRODUCTION The chaotic dynamics observed only in nonlinear systems have been largely defined by oscillations which are sensitive to initial conditions [1]. Lorenz and Rossler systems are pioneering simple chaotic systems discovered with a lot of interesting properties that can model physical systems [1]-[2]. This relatively new dynamical behaviour has since been discovered in other disciplines such as engineering, science and economics. In order to understand fully most nonlinear phenomenon in nature through interaction of systems, the control and synchronization of chaotic oscillations is vital. The process of controlling and synchronising chaotic systems has attracted much attention since its discovery in less than twenty years [3]. The work of Pecora and Caroll [4] generated a wider research in synchronization since it entails the synchronization of two identical chaotic systems with different initial conditions.A number of methods of synchronization have been proposed since the pioneering work of Pecora and Caroll such as complete synchronization, generalized synchronization, phase synchronization, lag synchronization, adaptive synchronization, time-scale synchronization, intermittent synchronization, projective synchronization and function projective synchronization [5]-[9]. Function projective synchronization deserves much attention since it has been found applicable and better in secure communication. Function projective synchronization implies that the master and slave oscillators could be synchronized up to a scaling function unlike a constant in the projective synchronization. The DOI : 10.5121/ijcseit.2014.4503 33
  • 2. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol. 4, No.5, October 2014 advantage is that it becomes more complex to determine the function used and as a result more secure communication is achieved under this scheme. In the present work, function projective synchronization of new chaotic reversal systems [10] with uncertain parameters using nonlinear adaptive controller has been investigated to demonstrate the effectiveness of this scheme as it applies in secure communication. The remaining part of this work is arranged as follows: section 2 is on the nonlinear adaptive controller designed to synchronize the new chaotic reversal systems, section 3 is on numerical simulations presented to demonstrate the robust nature of the scheme, and section 4 is the conclusion of the paper. In the present section, we examine briefly the dynamics of the new deterministic model for chaotic reversal [10]. 34 2. ADAPTIVE CONTROL SCHEME We have a new deterministic model for chaotic reversal by C. Gissinger [10] given by: ………. (1) Where and are the states and are unknown parameters. The system (1) is chaotic when the parameter values are taken as: and as shown in figure 1. Strange Attractor of the New Chaotic Reversal System -5 0 5 -5 0 4 2 0 -2 5 x 1 3 x 2 x Figure 1: The system (1) is taken as master system, and the slave system with the adaptive control scheme is taken as ………. (2)
  • 3. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol. 4, No.5, October 2014 Where are the parameters of the slave which needs to be estimated and are the nonlinear controllers such that the two new chaotic reversal systems are function projective synchronized in the sense that 35 ……… (3) Where is the scaling function. From system (1) and (2) we get the error dynamical system which can be written as ……… (4) Where In order to stabilize the error variables of system (3) at the origin, we propose the adaptive control law and the parameter update law for system (3) as follows …….(5) And the update rule for the three uncertain parameters are ……….. (6) Where and Theorem For the given scaling function , the function projective synchronization between the master system (1) and the slave system (2) can be achieved if the nonlinear controller (5) and the update law (6) are adopted. Proof We construct the following Lyapunov function Calculating the time derivative of V along the trajectory of error system (4), we have
  • 4. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol. 4, No.5, October 2014 36 … (8) + + + [ Where , and . It is evident that is negative definite and if and only if . By the Lyapunov stability theory, the function projective synchronization is achieved. This ends the proof. 3. NUMERICAL SIMULATIONS The numerical simulations to verify the effectiveness of the proposed function projective synchronization using the adaptive controllers are carried out by the fourth-order Runge-Kutta method. This method is used to solve the master system (1) and the slave system (2) with time step size . The initial conditions of the master system are . The scaling function is chosen as and . The figure 2 shows that the error variables tend to zero with . Figure 3 shows that the estimated values of the uncertain parameters converge to as . 300 250 200 150 100 50 0 0 2 4 6 8 10 12 14 16 18 20 Time / s e 1
  • 5. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol. 4, No.5, October 2014 37 5 4 3 2 1 0 -1 0 2 4 6 8 10 12 14 16 18 20 Time /s e 2 10 8 6 4 2 0 0 2 4 6 8 10 12 14 16 18 20 Time /s e 3 Figure 2: Error dynamics between master system (1) and the slave system (2) 100 0 -100 -200 -300 0 2 4 6 8 10 12 14 16 18 20 Time /s a 1
  • 6. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol. 4, No.5, October 2014 38 4 3 2 1 0 -1 0 2 4 6 8 10 12 14 16 18 20 Time /s b 1 12 10 8 6 4 2 0 0 2 4 6 8 10 12 14 16 18 20 Time /s c 1 Figure 3: The time evolution of the estimated parameters 4. CONCLUSION In the present work we have demonstrated the application of function projective synchronization in synchronizing the new chaotic reversal systems with uncertain parameters. The Lyapunov stability theory was used to design the adaptive synchronization controllers with associated parameter update laws to stabilize the error dynamics between the master and the slave chaotic oscillators. All the theoretical investigations have been verified by numerical simulations to proof the effectiveness of the scheme. REFERENCES [1] Lorenz, E.N. (1963) “Deterministic nonperiodic flow,” J. Atmos. Phys. Vol. 20, pp 131-141. [2] Rössler, O.E. (1976) “An equation for continuous chaos,” Physics Letters A, Vol. 57, pp 397-398. [3] Junbiao Guan, (2012 )‘’Function projective synchronization of a class of chaotic systems with uncertain parameters’’, Hindawi Publishing Corp., Article ID 431752, [4] L. M. Pecora and T. L. Carroll, (1990) “Synchronization in chaotic systems,” Physical Review Letters, vol. 64, no. 8, pp. 821–824,. [5] M. Rosenblum, A. Pikovsky, and J. Kurths, (1996) “Phase synchronization of chaotic oscillators,” Physical Review Letters, vol. 76, pp. 1804–1807,. [6] H. Taghvafard and G. H. Erjaee, (2011)“Phase and anti-phase synchronization of fractional order chaotic systems via active control,” Communications in Nonlinear Science and Numerical Simulation, vol. 16, no. 10, pp. 4079–4088,. [7] R. Mainieri and J. Rehacek, (1999)“Projective synchronization in three-dimensional chaotic systems,” Physical Review Letters, vol. 82, pp. 3042–3045,.
  • 7. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol. 4, No.5, October 2014 [8] Junbiao Guan, (2010) “Synchronization control of two different chaotic systems with known and 39 unknown parameters,” Chinese Physics Letters, vol. 27, Article ID 020502,. [9] L. Runzi, (2008) “Adaptive function project synchronization of Rossler hyperchaotic system with uncertain parameters,” Physics Letters. A, vol. 372, no. 20, pp. 3667–3671, [10] Gissinger, C. (2012) ‘’ A new deterministic model for chaotic reversals, ’’ Euro. Phy. J. B 85:137, pp 1-12. Author Ojoniyi, Olurotimi Seyi is currently on a Ph.D programme in nonlinear dynamics and chaos at the department of Physics of the University of Agriculture, Abeokuta, Ogun State, Nigeria. He holds a M.Sc, degree in Physics from the University of Ibadan, Ibadan, Nigeria and is currently an academic Staff of Physics and Telecommunications department of Tai Solarin University of Education, Ijagun, Ogun State, Nigeria.