SlideShare a Scribd company logo
International Journal of Power Electronics and Drive System (IJPEDS)
Vol. 8, No. 4, December 2017, pp. 1814~1821
ISSN: 2088-8694, DOI: 10.11591/ijpeds.v8i4.pp1814-1821  1814
Journal homepage: http://iaesjournal.com/online/index.php/IJPEDS
The Control Structure for DC Motor based on the Flatness
Control
Thang Nguyen Trong
Departement of Industrial Electrical Engineering and Automation, Haiphong Private University, Vietnam
Article Info ABSTRACT
Article history:
Received Sep 8, 2017
Revised Nov 23, 2017
Accepted Nov 30, 2017
This article presents the new control structure for a Direct Current Motor
(DC Motor) using the flatness-control principle. Basic on the mathematical
model of DC Motors, the author demonstrates the application ability of the
fatness-control theory to control the DC Motor, and then calculates the
parameters and proposes the structure of the flatness-controller. The
proposed structure is built and ran on Matlab-Simulink software to verify the
system efficiency. The simulation results show that the quality of the control
system is very good, especially in case of the flatness controller combined
with PID controller to eliminate static error when the parameters of the DC
Motor have been not known accurately.
Keyword:
Control structure
DC motor
Electric
Flatness cotroller
PID controller Copyright © 2017 Institute of Advanced Engineering and Science.
All rights reserved.
Corresponding Author:
Thang Nguyen Trong,
Departement of Industrial Electrical Engineering and Automation,
Haiphong Private University,
36 Danlap street, Haiphong, Vietnam.
Email: thangnt@hpu.edu.vn
1. INTRODUCTION
DC Motor is one of the traditional electric machines, is appeared in the late of 19th century. In
compared to the other electric machine such as induction machine [1], [2], brushless DC motors [3], the DC
Motor has the internal advantages such as simple control, large electromagnetic torque, the ability to adjust
the speed with the wide range [4]. So, DC Motors are still commonly used in industrial fields such as steel
rolling, transportation, mining, defense, construction [5-7]. Thus, improving the quality of DC Motor control
system is essential. There are many studies to control DC Motors [8-11], the most popular is still the method
using PID controllers. However, in many working modes of DC Motors, the nonlinear of DC Motor is high,
which reduces the quality of control system.
There are several solutions for controlling the nonlinear object such as the input-output linearization
method [12], the sliding mode control technique [13], the backstepping control technique [14], etc. The
drawback of the above methods is the existence of the chattering phenomenon or the difficult problem in the
choice of appropriate Lyapunov function. Therefore, the author proposes a suitable control system to improve
the control quality of a DC Motor, which is a control system based on flatness principle. With this method, it
is easy to decouple the input and output, directly identify each system variables by choosing the appropriate
system output variables.
The Flatness Control Theory is a new method control for nonlinear object [15], [16], promising a
high quality of control [17], being attracted by scientists around the world. Many researchers have come up
with different definitions of flatness control systems, but in general, the flatness control is regarded as a
useful tool for the nonlinear control system [18]. The most specific of the flatness system is the existence of
assemblage of z, through the z variables and the differential of the z variables, all state variables, and input
IJPEDS ISSN: 2088-8694 
The Control Structure for DC Motor based on the Flatness Control (Thang Nguyen Trong)
1815
variables can be determined. So we can determine in advance the trajectory of the input from the desired
trajectory of the output.
2. THE STRUCTURE CONTROL BASED ON FLATNESS CONTROL THEORY
2.1. The Basis of Flatness Control Theory
Flatness control theory is applied to control a lot of nonlinear objects which have the status equation
is written as follows [15], [19]:
)
,
( u
x
f
x 
 (1)
With
T
m
u
u
u
u )
,..
,
( 2
1
 is the input variables,
T
n
x
x
x
x )
,..
,
( 2
1
 is the status variables.
The system (1) is called a flatness system if there are a set of variables )
,...,
,
( 2
1 m
z
z
z
z  called
the flat outputs, satisfying three conditions as follows:
a. Existing a function h, which is satisfied:
)
,...
,
( )
(
u
u
x
h
z  (2)
b. All input variables and state variables can be determined from the variable z, which means that
there are function A and function B, which are satisfied:
)
,...
,
( )
(
z
z
z
A
x 
 (3)
)
,...
,
( )
1
( 
 
z
z
z
B
u  (4)
c. All variables of z are independently differential together, which means that there is not the
function G, which is satisfied: 0
)
,...
,
( )
(

m
z
z
z
G 
There are many control systems that satisfy the properties of flatness systems such as electric
motors, chemical reactors, cranes, transmission systems, eg.
2.2. Demonstrating the Flatness of DC Motors
The structure of a separately excited DC Motor is shown in Figure 1, which includes:
a. The armature coil in the rotor
b. The excitation coil in the stator
Figure 1. The structure of the separately excited DC Motor
To demonstrate a DC Motor is flatness system, the first we have to definite the mathematical model
of the DC Motor, in order to prove DC Motor satisfies the conditions of the flatness system. The
mathematical equations of DC Motors are as follows:
a. The equation of voltage:
E
dt
di
L
i
R
u a
a
a
a
a 

 (V) (5)
With a
u is the armature voltage; a
a L
R , is the armature resistance and inductance.
 ISSN: 2088-8694
IJPEDS Vol. 8, No. 4, December 2017 : 1814 – 1821
1816
b. The equation of the Electromotive:

 ).
.
( f
af
E i
L
K
E 
 (V) (6)
With KE is the voltage coefficient, ω is the rotor speed, af
L is the field armature mutual inductance,
f
i is the field current.
c. The motion equation of the DC Motor:
f
m
L
e T
B
T
T
dt
d
J 


 
 (N.m) (7)
Where J is the inertia, m
B is the viscous friction coefficient, f
T is the coulomb friction torque, e
T
is the electromechanical torque, L
T is the torque applied to the shaft.
d. The equation of electromechanical torque:
a
f
af
a
T
e i
i
L
L
K
T ).
.
(

 (N.m) (8)
With T
K is the torque coefficient.
From the equations of DC Motors, changing into the state equations with the state variables are the
armature current and the speed ( )
,
( 
a
i
x  , a
u
u  ):















f
L
m
a
T
a
a
a
E
a
a
a
a
T
J
T
J
J
B
i
J
K
dt
d
u
L
L
K
i
L
R
dt
di
1
1
1


 (9)
Selecting the flat output variable is 

z , it is easy to prove that the DC Motor is flatness under
three conditions:
e. The first condition is existing the function h satisfied: )
,...
,
( )
(
u
u
x
h
z  . From the
Equation (9), it is easy to see that the first condition is satisfied.
f. The second condition, there are the function A and the function B satisfied: )
,...
,
( )
(
z
z
z
A
x 
 ,
)
,...
,
( )
1
( 
 
z
z
z
B
u  .
Transforming the Equation (9), we have:
    )
,
(
1
1
1
z
z
G
T
T
z
B
z
J
K
T
T
B
J
K
i f
L
m
T
f
L
m
T
a 

 







 
 (10)
So )
,
(
)
,
( 

 
A
i
x a 

Transforming the Equation (9), we have:
 
  )
,
,
(
2
)
.
(
)
.
(
z
z
z
G
z
K
T
z
B
z
J
K
L
T
T
z
B
z
J
K
R
K
T
B
J
K
L
T
T
B
J
K
R
u
E
L
m
T
a
f
L
m
T
a
E
L
m
E
a
f
L
m
T
a
a





























 




(11)
So )
,
,
( z
z
z
B
u
u a 




So we can conclude that the second condition is satisfied
g. The third condition, all variables of z are independently differential together, this is obvious
because the flat outputs are selected with only one variable.
So we have concluded that DC Motors are flatness systems with flat output is 

z
IJPEDS ISSN: 2088-8694 
The Control Structure for DC Motor based on the Flatness Control (Thang Nguyen Trong)
1817
2.3. Designing the Flatness Controller
Based on the equations of DC Motors, we construct the stages of the flatness controller. From the
Equation (9), we design the speed controller (calculating the current a
i ). From the Equation (9), we design
the current controller (calculating the voltage a
u ).
The equation of speed controller:











 f
L
m
T
a T
T
B
dt
d
J
K
i *
*
* 1

 (12)
The equation of current controller:
*
* *

E
a
a
a
a
a K
dt
di
L
i
R
u 

 (13)
The block diagram of flatness control system for DC Motor is shown in Figure 2:
Figure 2. The block diagram of flatness control system for DC Motor
2.4. Building the Model Simulation
The control system diagram is constructed as shown in Figure 3.
Figure 3. The simulation n diagram of the control system with the flatness controller
In order to achieve objective results, in the diagram we use the DC Motor model available in the
Matlab-Simulink library, the parameters of DC Motor are shown in Table 1.
 ISSN: 2088-8694
IJPEDS Vol. 8, No. 4, December 2017 : 1814 – 1821
1818
Table 1. The parameters of DC Motor
Ra() La(H) Rf() Lf(H) Laf(H) J(kg.m^2) Bm(N.m.s) Tf(N.m)
0.5 0.015 220 140 1.7 1.2 0.5 20
Based on the model and parameters of DC Motor, the control block is built as follows:
a. The block of speed control is built based on the Equation (12), shown in Figure 4
b. The speed control block is built based on the Equation (13), shown in Figure 5.
Figure 4. The Speed Control Block Figure 5. The Current Control Block
2.5. The Simulated Results
Running the system with the initial set speed )
/
(
120 s
rad

 , then changing the value of set
speed at time t = 1.5s and t = 3s ( )
/
(
150 s
rad

 and )
/
(
180 s
rad

 ). Load initially with the
torque of the shaft )
.
(
50 m
N
TL  , then at time t = 4.5(s) and t = 5.5(s), we increase L
T to 100 (N.m) and
200 (N.m). The simulation results are shown in Figure 6(a). The simulation results show that the change of
speed values meet very good requirements.
For clarity, we study in more detail the graph of the set speed and actual speed in Figure (6b). From
the graph (6b), we see that the actual speed value is very close to the set speed value.
The change in speed depends on the load is shown in Figure (6c). Simulation results show that the
system is very high quality, the speed of the Motor is almost unchanged when the torque changes.
From the results above, we see that the proposed method with the simple control algorithm has the
high efficiency.
Figure 6. The simulated results with the flatness controller
IJPEDS ISSN: 2088-8694 
The Control Structure for DC Motor based on the Flatness Control (Thang Nguyen Trong)
1819
3. THE PROBLEM OF THE PARAMETER ERROR OF THE MOTOR MODEL
The simulation results in part 2 show that the quality of the control system is perfect, because of the
assume that we know exactly the parameters of the DC Motor. However, in reality, it is impossible to know
the parameters of DC exactly, so the quality of control system is not perfect as above. To check the control
quality when DC parameter is not known exactly, we assume that some parameters of the DC Motor are
changed, the parameter of the DC Motor, after changed is shown in Table 2:
Table 2. The parameters of DC Motor after changed
Ra() La(H) Rf() Lf(H) Laf(H) J(kg.m^2) Bm(N.m.s) Tf(N.m)
0.55 0.016 220 145 1.6 1.3 0.6 20
Running the system model, the response of the actual speed and set speed is shown in Figure 7. The
results show that there is a difference between the set speed and the actual speed. To eliminate this
difference, we add a PID controller connected in parallel with the flatness controller. The parallel control
diagram is shown in Figure 8. The simulation model with the additional PID controller is shown in Figure 9.
Figure 7. The simulated results when the DC parameter is not known exactly
Figure 8. The parallel control diagram
 ISSN: 2088-8694
IJPEDS Vol. 8, No. 4, December 2017 : 1814 – 1821
1820
Figure 9. The simulation diagram of the control system with the additional PID controller
Running the model with the additional PID controller and Kp=3, Ki=0.5, the simulation results are
shown in Figure 10. The results show that when changing the set speed, the actual speed of DC Motor is very
close to the set speed, and when the torque of the shaft changes, the speed of DC Motor is not affected much.
So the flatness control system for DC Motor with the support of the PID controller has worked very well.
Figure 10. The simulated results with the additional PID controller
4. CONCLUSION
In this paper, the author has successfully built the control system for DC Motor based on a flatness
control. The simulation results demonstrate that the system with the flatness controller works very well if we
know exactly the parameters of DC Motor. However, in fact, the parameters of the DC Motor have not
known accurately, so there is the error between set speed and actual speed when only the flatness control is
applied. A PID controller has been put into operation in parallel with the flat controller to eliminate their
error. The simulation results show that the quality of the whole system is very good and work effectively.
The actual speed of DC Motor is very close to the desired speed with the small transaction time. More, if the
load or the torque of the DC motor shaft is changed but the rotor speed of DC motor is not affected much.
Thus, the proposed system can be applied well in motion control applications that require the high-quality of
the speed control.
REFERENCES
[1] Abdelhak, B., & Bachir, B., “A High gain observer based sensorless nonlinear control of induction machine,”
International Journal of Power Electronics and Drive Systems, 5(3), 305, 2015.
IJPEDS ISSN: 2088-8694 
The Control Structure for DC Motor based on the Flatness Control (Thang Nguyen Trong)
1821
[2] Gunabalan, R., & Subbiah, V., “Speed Sensorless Vector Control of Induction Motor Drive with PI and Fuzzy
Controller,” International Journal of Power Electronics and Drive Systems, 5(3), 315, 2015.
[3] Park, J. S., & Lee, K. D., “Design and Implementation of BLDC Motor with Integrated Drive
Circuit,” International Journal of Power Electronics and Drive Systems (IJPEDS), 8(3), 1109-1116, 2017.
[4] Hughes, Austin, and Bill Drury, “Electric Motors and drives: fundamentals, types and applications,” Newnes,
2013.
[5] Shieh, N. C., and P. C. Tung, "Robust output tracking control of a linear DC brushless Motor for transportation in
manufacturing system", IEE Proceedings-Electric Power Applications, 2001,pp. 119-124.
[6] Pickrell, Don, and Paul Schimek, "Growth in Motor vehicle ownership and use: Evidence from the Nationwide
Personal Transportation Survey", Journal of Transportation and Statistics, vol.2.1, pp.1-17, 1999.
[7] Fletcher, David I., and John H. Beynon, "Development of a machine for closely controlled rolling contact fatigue
and wear testing", Journal of testing and evaluation, Vol 28.4, pp. 267-275, 2000.
[8] Bosco, Maycon Chimini, et al, "Estimation of parameters and tuning of a speed PI of permanent magnet DC Motor
using differential evolution", Electric Machines and Drives Conference (IEMDC), IEEE International,2017,pp.1-6.
[9] Yao, Jianyong, Zongxia Jiao, and Dawei Ma, "Adaptive robust control of DC Motors with extended state observer",
IEEE Transactions on Industrial Electronics Vol 61.7 ,2014, pp. 3630-3637.
[10] Xue, Dingyu, Chunna Zhao, and YangQuan Chen, "Fractional order PID control of a DC-Motor with elastic shaft:
a case study", American Control Conference, IEEE, 2006, pp.1-6
[11] Thomas, Neenu, and Dr P. Poongodi, "Position control of DC Motor using genetic algorithm based PID
controller", Proceedings of the World Congress on Engineering, 2009, vol. 2, pp. 1-3.
[12] Yazdanpanah, R., Soltani, J., & Markadeh, G. A., “Nonlinear torque and stator flux controller for induction motor
drive based on adaptive input–output feedback linearization and sliding mode control”, Energy Conversion and
management, 49(4), 541-550, 2008.
[13] Abdelmadjid, G., Seghir, B. M., Ahmed, S., & Youcef, M., “Sensorless sliding mode vector control of induction
motor drives,” International Journal of Power Electronics and Drive Systems, 2(3), 277, 2012.
[14] Trabelsi, R., Khedher, A., Mimouni, M. F., & M'sahli, F., “Backstepping control for an induction motor using an
adaptive sliding rotor-flux observer,” Electric Power Systems Research, 93, 1-15, 2012.
[15] Martin, P., Murray, R. M., & Rouchon, P., “Flat systems, equivalence and trajectory generation,” 2003.
[16] Xian-lin, C. H. E. N, "Flatness control in new generation high-tech mills for wide strip rolling", Journal of
University of Science and Technology Beijing, Vol 19, pp.1-5, 1997.
[17] Jelali, Mohieddine, "Performance assessment of control systems in rolling mills–application to strip thickness and
flatness control", Journal of Process Control, Vol 17.10,pp. 805-816, 2007.
[18] Farid, B., Waffa, B., & Bachir, B. A., “Flatness Based Nonlinear Sensorless Control of Induction Motor
Systems,” International Journal of Power Electronics and Drive Systems, 7(1), 265, 2016.
[19] Delaleau, Emmanuel, and Aleksandar M. Stankovic, "Flatness-based hierarchical control of the PM synchronous
Motor", American Control Conference, Proceedings, Vol. 1, IEEE, 2004, pp. 65-70.
BIOGRAPHY OF AUTHOR
Thang Nguyen Trong received the B.Eng.degree in Automation Control from Hanoi University of
Science and Technology in 2005, and Ph.D.degrees in Control Engineering and Automation from
University of Transport and Communications, Vietnam in 2014. He is currently the Head of
Department of Industrial Electrical Engineering and Automation, Haiphong Privite University,
Vietnam. He is a member of Instittute of Electrical and Electronic Engineers (IEEE), his research
interests include automattion control theory, electric drive control, power generation systems on
ships.

More Related Content

PDF
Real Time Implementation of Fuzzy Adaptive PI-sliding Mode Controller for Ind...
PDF
Iaetsd modelling of one link flexible arm manipulator using
PDF
Discrete Time Optimal Tracking Control of BLDC Motor
PDF
Flatness Based Nonlinear Sensorless Control of Induction Motor Systems
DOC
Basic Control System unit6
PDF
Iaetsd modelling and controller design of cart inverted pendulum system using...
PDF
MODELLING AND SIMULATION OF INVERTED PENDULUM USING INTERNAL MODEL CONTROL
PPSX
Backstepping control of cart pole system
Real Time Implementation of Fuzzy Adaptive PI-sliding Mode Controller for Ind...
Iaetsd modelling of one link flexible arm manipulator using
Discrete Time Optimal Tracking Control of BLDC Motor
Flatness Based Nonlinear Sensorless Control of Induction Motor Systems
Basic Control System unit6
Iaetsd modelling and controller design of cart inverted pendulum system using...
MODELLING AND SIMULATION OF INVERTED PENDULUM USING INTERNAL MODEL CONTROL
Backstepping control of cart pole system

What's hot (18)

PPTX
Queues presentation
PDF
Neural Network Control Based on Adaptive Observer for Quadrotor Helicopter
PDF
Hexacopter using MATLAB Simulink and MPU Sensing
PDF
Raymond.Brunkow-Project-EEL-3657-Sp15
PDF
Real-time PID control of an inverted pendulum
PDF
Control system objective type questions
PDF
Inverted Pendulum Control: A Brief Overview
PDF
Metal cutting tool position control using static output feedback and full sta...
PDF
07 15 sep14 6532 13538-1-rv-edit_
PDF
ENHANCED DATA DRIVEN MODE-FREE ADAPTIVE YAW CONTROL OF UAV HELICOPTER
PDF
A Suitable Structure to Control the System of Quad-rotor Miniature Aerial Veh...
PDF
Design and control of ems magnetic levitation train using fuzzy mras and pid ...
PDF
D05532531
PDF
DEVELOPMENT AND IMPLEMENTATION OF A ADAPTIVE FUZZY CONTROL SYSTEM FOR A VTOL ...
PDF
Controller design of inverted pendulum using pole placement and lqr
DOCX
DOCX
Control system objective_type_questions
PDF
Stability Control of an Autonomous Quadcopter through PID Control Law
Queues presentation
Neural Network Control Based on Adaptive Observer for Quadrotor Helicopter
Hexacopter using MATLAB Simulink and MPU Sensing
Raymond.Brunkow-Project-EEL-3657-Sp15
Real-time PID control of an inverted pendulum
Control system objective type questions
Inverted Pendulum Control: A Brief Overview
Metal cutting tool position control using static output feedback and full sta...
07 15 sep14 6532 13538-1-rv-edit_
ENHANCED DATA DRIVEN MODE-FREE ADAPTIVE YAW CONTROL OF UAV HELICOPTER
A Suitable Structure to Control the System of Quad-rotor Miniature Aerial Veh...
Design and control of ems magnetic levitation train using fuzzy mras and pid ...
D05532531
DEVELOPMENT AND IMPLEMENTATION OF A ADAPTIVE FUZZY CONTROL SYSTEM FOR A VTOL ...
Controller design of inverted pendulum using pole placement and lqr
Control system objective_type_questions
Stability Control of an Autonomous Quadcopter through PID Control Law
Ad

Similar to The Control Structure for DC Motor based on the Flatness Control (20)

PDF
Sliding mode control-based system for the two-link robot arm
PDF
Direct torque control and dynamic performance of induction motor using fract...
PDF
Unity Feedback PD Controller Design for an Electronic Throttle Body
PDF
Fractional-order sliding mode controller for the two-link robot arm
PDF
Min Max Model Predictive Control for Polysolenoid Linear Motor
PDF
Contribution to the Improvement of the Performances of Doubly Fed Induction M...
PDF
The Neural Network-Combined Optimal Control System of Induction Motor
PDF
Experiment based comparative analysis of stator current controllers using pre...
PDF
F010424451
PDF
SPEED AND TORQUE CONTROL OF AN INDUCTION MOTOR WITH ANN BASED DTC
PDF
LIGHTWEIGHT MOBILE WEB SERVICE PROVISIONING FOR THE INTERNET OF THINGS MEDIATION
PDF
A New Induction Motor Adaptive Robust Vector Control based on Backstepping
PDF
Comparison of Estimated Torques Using Low Pass Filter and Extended Kalman Fil...
PDF
Experimental dataset to develop a parametric model based of DC geared motor i...
PDF
Image Based Visual Servoing for Omnidirectional Wheeled Mobile Robots in Volt...
PDF
Design and implementation speed control system of DC Motor based on PID contr...
PDF
Kinematics Analysis of Parallel Mechanism Based on Force Feedback Device
PDF
High performance DC/DC buck converter using sliding mode controller
PDF
Backstepping control of two-mass system using induction motor drive fed by vo...
PDF
D0372027037
Sliding mode control-based system for the two-link robot arm
Direct torque control and dynamic performance of induction motor using fract...
Unity Feedback PD Controller Design for an Electronic Throttle Body
Fractional-order sliding mode controller for the two-link robot arm
Min Max Model Predictive Control for Polysolenoid Linear Motor
Contribution to the Improvement of the Performances of Doubly Fed Induction M...
The Neural Network-Combined Optimal Control System of Induction Motor
Experiment based comparative analysis of stator current controllers using pre...
F010424451
SPEED AND TORQUE CONTROL OF AN INDUCTION MOTOR WITH ANN BASED DTC
LIGHTWEIGHT MOBILE WEB SERVICE PROVISIONING FOR THE INTERNET OF THINGS MEDIATION
A New Induction Motor Adaptive Robust Vector Control based on Backstepping
Comparison of Estimated Torques Using Low Pass Filter and Extended Kalman Fil...
Experimental dataset to develop a parametric model based of DC geared motor i...
Image Based Visual Servoing for Omnidirectional Wheeled Mobile Robots in Volt...
Design and implementation speed control system of DC Motor based on PID contr...
Kinematics Analysis of Parallel Mechanism Based on Force Feedback Device
High performance DC/DC buck converter using sliding mode controller
Backstepping control of two-mass system using induction motor drive fed by vo...
D0372027037
Ad

More from International Journal of Power Electronics and Drive Systems (20)

PDF
Adaptive backstepping controller design based on neural network for PMSM spee...
PDF
Classification and direction discrimination of faults in transmission lines u...
PDF
Integration of artificial neural networks for multi-source energy management ...
PDF
Rotating blade faults classification of a rotor-disk-blade system using artif...
PDF
Artificial bee colony algorithm applied to optimal power flow solution incorp...
PDF
Soft computing and IoT based solar tracker
PDF
Comparison of roughness index for Kitka and Koznica wind farms
PDF
Primary frequency control of large-scale PV-connected multi-machine power sys...
PDF
Performance of solar modules integrated with reflector
PDF
Generator and grid side converter control for wind energy conversion system
PDF
Wind speed modeling based on measurement data to predict future wind speed wi...
PDF
Comparison of PV panels MPPT techniques applied to solar water pumping system
PDF
Prospect of renewable energy resources in Bangladesh
PDF
A novel optimization of the particle swarm based maximum power point tracking...
PDF
Voltage stability enhancement for large scale squirrel cage induction generat...
PDF
Electrical and environmental parameters of the performance of polymer solar c...
PDF
Short and open circuit faults study in the PV system inverter
PDF
A modified bridge-type nonsuperconducting fault current limiter for distribut...
PDF
The new approach minimizes harmonics in a single-phase three-level NPC 400 Hz...
PDF
Comparison of electronic load using linear regulator and boost converter
Adaptive backstepping controller design based on neural network for PMSM spee...
Classification and direction discrimination of faults in transmission lines u...
Integration of artificial neural networks for multi-source energy management ...
Rotating blade faults classification of a rotor-disk-blade system using artif...
Artificial bee colony algorithm applied to optimal power flow solution incorp...
Soft computing and IoT based solar tracker
Comparison of roughness index for Kitka and Koznica wind farms
Primary frequency control of large-scale PV-connected multi-machine power sys...
Performance of solar modules integrated with reflector
Generator and grid side converter control for wind energy conversion system
Wind speed modeling based on measurement data to predict future wind speed wi...
Comparison of PV panels MPPT techniques applied to solar water pumping system
Prospect of renewable energy resources in Bangladesh
A novel optimization of the particle swarm based maximum power point tracking...
Voltage stability enhancement for large scale squirrel cage induction generat...
Electrical and environmental parameters of the performance of polymer solar c...
Short and open circuit faults study in the PV system inverter
A modified bridge-type nonsuperconducting fault current limiter for distribut...
The new approach minimizes harmonics in a single-phase three-level NPC 400 Hz...
Comparison of electronic load using linear regulator and boost converter

Recently uploaded (20)

PPTX
CARTOGRAPHY AND GEOINFORMATION VISUALIZATION chapter1 NPTE (2).pptx
PDF
Operating System & Kernel Study Guide-1 - converted.pdf
PPTX
M Tech Sem 1 Civil Engineering Environmental Sciences.pptx
PPTX
Recipes for Real Time Voice AI WebRTC, SLMs and Open Source Software.pptx
PDF
July 2025 - Top 10 Read Articles in International Journal of Software Enginee...
PPTX
Construction Project Organization Group 2.pptx
PDF
Well-logging-methods_new................
PDF
Digital Logic Computer Design lecture notes
PPTX
UNIT 4 Total Quality Management .pptx
PDF
PRIZ Academy - 9 Windows Thinking Where to Invest Today to Win Tomorrow.pdf
PDF
Mitigating Risks through Effective Management for Enhancing Organizational Pe...
PPT
CRASH COURSE IN ALTERNATIVE PLUMBING CLASS
PPT
Project quality management in manufacturing
PPTX
CH1 Production IntroductoryConcepts.pptx
PDF
R24 SURVEYING LAB MANUAL for civil enggi
PDF
composite construction of structures.pdf
PPTX
Foundation to blockchain - A guide to Blockchain Tech
DOCX
ASol_English-Language-Literature-Set-1-27-02-2023-converted.docx
PPTX
Engineering Ethics, Safety and Environment [Autosaved] (1).pptx
PDF
Mohammad Mahdi Farshadian CV - Prospective PhD Student 2026
CARTOGRAPHY AND GEOINFORMATION VISUALIZATION chapter1 NPTE (2).pptx
Operating System & Kernel Study Guide-1 - converted.pdf
M Tech Sem 1 Civil Engineering Environmental Sciences.pptx
Recipes for Real Time Voice AI WebRTC, SLMs and Open Source Software.pptx
July 2025 - Top 10 Read Articles in International Journal of Software Enginee...
Construction Project Organization Group 2.pptx
Well-logging-methods_new................
Digital Logic Computer Design lecture notes
UNIT 4 Total Quality Management .pptx
PRIZ Academy - 9 Windows Thinking Where to Invest Today to Win Tomorrow.pdf
Mitigating Risks through Effective Management for Enhancing Organizational Pe...
CRASH COURSE IN ALTERNATIVE PLUMBING CLASS
Project quality management in manufacturing
CH1 Production IntroductoryConcepts.pptx
R24 SURVEYING LAB MANUAL for civil enggi
composite construction of structures.pdf
Foundation to blockchain - A guide to Blockchain Tech
ASol_English-Language-Literature-Set-1-27-02-2023-converted.docx
Engineering Ethics, Safety and Environment [Autosaved] (1).pptx
Mohammad Mahdi Farshadian CV - Prospective PhD Student 2026

The Control Structure for DC Motor based on the Flatness Control

  • 1. International Journal of Power Electronics and Drive System (IJPEDS) Vol. 8, No. 4, December 2017, pp. 1814~1821 ISSN: 2088-8694, DOI: 10.11591/ijpeds.v8i4.pp1814-1821  1814 Journal homepage: http://iaesjournal.com/online/index.php/IJPEDS The Control Structure for DC Motor based on the Flatness Control Thang Nguyen Trong Departement of Industrial Electrical Engineering and Automation, Haiphong Private University, Vietnam Article Info ABSTRACT Article history: Received Sep 8, 2017 Revised Nov 23, 2017 Accepted Nov 30, 2017 This article presents the new control structure for a Direct Current Motor (DC Motor) using the flatness-control principle. Basic on the mathematical model of DC Motors, the author demonstrates the application ability of the fatness-control theory to control the DC Motor, and then calculates the parameters and proposes the structure of the flatness-controller. The proposed structure is built and ran on Matlab-Simulink software to verify the system efficiency. The simulation results show that the quality of the control system is very good, especially in case of the flatness controller combined with PID controller to eliminate static error when the parameters of the DC Motor have been not known accurately. Keyword: Control structure DC motor Electric Flatness cotroller PID controller Copyright © 2017 Institute of Advanced Engineering and Science. All rights reserved. Corresponding Author: Thang Nguyen Trong, Departement of Industrial Electrical Engineering and Automation, Haiphong Private University, 36 Danlap street, Haiphong, Vietnam. Email: thangnt@hpu.edu.vn 1. INTRODUCTION DC Motor is one of the traditional electric machines, is appeared in the late of 19th century. In compared to the other electric machine such as induction machine [1], [2], brushless DC motors [3], the DC Motor has the internal advantages such as simple control, large electromagnetic torque, the ability to adjust the speed with the wide range [4]. So, DC Motors are still commonly used in industrial fields such as steel rolling, transportation, mining, defense, construction [5-7]. Thus, improving the quality of DC Motor control system is essential. There are many studies to control DC Motors [8-11], the most popular is still the method using PID controllers. However, in many working modes of DC Motors, the nonlinear of DC Motor is high, which reduces the quality of control system. There are several solutions for controlling the nonlinear object such as the input-output linearization method [12], the sliding mode control technique [13], the backstepping control technique [14], etc. The drawback of the above methods is the existence of the chattering phenomenon or the difficult problem in the choice of appropriate Lyapunov function. Therefore, the author proposes a suitable control system to improve the control quality of a DC Motor, which is a control system based on flatness principle. With this method, it is easy to decouple the input and output, directly identify each system variables by choosing the appropriate system output variables. The Flatness Control Theory is a new method control for nonlinear object [15], [16], promising a high quality of control [17], being attracted by scientists around the world. Many researchers have come up with different definitions of flatness control systems, but in general, the flatness control is regarded as a useful tool for the nonlinear control system [18]. The most specific of the flatness system is the existence of assemblage of z, through the z variables and the differential of the z variables, all state variables, and input
  • 2. IJPEDS ISSN: 2088-8694  The Control Structure for DC Motor based on the Flatness Control (Thang Nguyen Trong) 1815 variables can be determined. So we can determine in advance the trajectory of the input from the desired trajectory of the output. 2. THE STRUCTURE CONTROL BASED ON FLATNESS CONTROL THEORY 2.1. The Basis of Flatness Control Theory Flatness control theory is applied to control a lot of nonlinear objects which have the status equation is written as follows [15], [19]: ) , ( u x f x   (1) With T m u u u u ) ,.. , ( 2 1  is the input variables, T n x x x x ) ,.. , ( 2 1  is the status variables. The system (1) is called a flatness system if there are a set of variables ) ,..., , ( 2 1 m z z z z  called the flat outputs, satisfying three conditions as follows: a. Existing a function h, which is satisfied: ) ,... , ( ) ( u u x h z  (2) b. All input variables and state variables can be determined from the variable z, which means that there are function A and function B, which are satisfied: ) ,... , ( ) ( z z z A x   (3) ) ,... , ( ) 1 (    z z z B u  (4) c. All variables of z are independently differential together, which means that there is not the function G, which is satisfied: 0 ) ,... , ( ) (  m z z z G  There are many control systems that satisfy the properties of flatness systems such as electric motors, chemical reactors, cranes, transmission systems, eg. 2.2. Demonstrating the Flatness of DC Motors The structure of a separately excited DC Motor is shown in Figure 1, which includes: a. The armature coil in the rotor b. The excitation coil in the stator Figure 1. The structure of the separately excited DC Motor To demonstrate a DC Motor is flatness system, the first we have to definite the mathematical model of the DC Motor, in order to prove DC Motor satisfies the conditions of the flatness system. The mathematical equations of DC Motors are as follows: a. The equation of voltage: E dt di L i R u a a a a a    (V) (5) With a u is the armature voltage; a a L R , is the armature resistance and inductance.
  • 3.  ISSN: 2088-8694 IJPEDS Vol. 8, No. 4, December 2017 : 1814 – 1821 1816 b. The equation of the Electromotive:   ). . ( f af E i L K E   (V) (6) With KE is the voltage coefficient, ω is the rotor speed, af L is the field armature mutual inductance, f i is the field current. c. The motion equation of the DC Motor: f m L e T B T T dt d J       (N.m) (7) Where J is the inertia, m B is the viscous friction coefficient, f T is the coulomb friction torque, e T is the electromechanical torque, L T is the torque applied to the shaft. d. The equation of electromechanical torque: a f af a T e i i L L K T ). . (   (N.m) (8) With T K is the torque coefficient. From the equations of DC Motors, changing into the state equations with the state variables are the armature current and the speed ( ) , (  a i x  , a u u  ):                f L m a T a a a E a a a a T J T J J B i J K dt d u L L K i L R dt di 1 1 1    (9) Selecting the flat output variable is   z , it is easy to prove that the DC Motor is flatness under three conditions: e. The first condition is existing the function h satisfied: ) ,... , ( ) ( u u x h z  . From the Equation (9), it is easy to see that the first condition is satisfied. f. The second condition, there are the function A and the function B satisfied: ) ,... , ( ) ( z z z A x   , ) ,... , ( ) 1 (    z z z B u  . Transforming the Equation (9), we have:     ) , ( 1 1 1 z z G T T z B z J K T T B J K i f L m T f L m T a               (10) So ) , ( ) , (     A i x a   Transforming the Equation (9), we have:     ) , , ( 2 ) . ( ) . ( z z z G z K T z B z J K L T T z B z J K R K T B J K L T T B J K R u E L m T a f L m T a E L m E a f L m T a a                                    (11) So ) , , ( z z z B u u a      So we can conclude that the second condition is satisfied g. The third condition, all variables of z are independently differential together, this is obvious because the flat outputs are selected with only one variable. So we have concluded that DC Motors are flatness systems with flat output is   z
  • 4. IJPEDS ISSN: 2088-8694  The Control Structure for DC Motor based on the Flatness Control (Thang Nguyen Trong) 1817 2.3. Designing the Flatness Controller Based on the equations of DC Motors, we construct the stages of the flatness controller. From the Equation (9), we design the speed controller (calculating the current a i ). From the Equation (9), we design the current controller (calculating the voltage a u ). The equation of speed controller:             f L m T a T T B dt d J K i * * * 1   (12) The equation of current controller: * * *  E a a a a a K dt di L i R u    (13) The block diagram of flatness control system for DC Motor is shown in Figure 2: Figure 2. The block diagram of flatness control system for DC Motor 2.4. Building the Model Simulation The control system diagram is constructed as shown in Figure 3. Figure 3. The simulation n diagram of the control system with the flatness controller In order to achieve objective results, in the diagram we use the DC Motor model available in the Matlab-Simulink library, the parameters of DC Motor are shown in Table 1.
  • 5.  ISSN: 2088-8694 IJPEDS Vol. 8, No. 4, December 2017 : 1814 – 1821 1818 Table 1. The parameters of DC Motor Ra() La(H) Rf() Lf(H) Laf(H) J(kg.m^2) Bm(N.m.s) Tf(N.m) 0.5 0.015 220 140 1.7 1.2 0.5 20 Based on the model and parameters of DC Motor, the control block is built as follows: a. The block of speed control is built based on the Equation (12), shown in Figure 4 b. The speed control block is built based on the Equation (13), shown in Figure 5. Figure 4. The Speed Control Block Figure 5. The Current Control Block 2.5. The Simulated Results Running the system with the initial set speed ) / ( 120 s rad   , then changing the value of set speed at time t = 1.5s and t = 3s ( ) / ( 150 s rad   and ) / ( 180 s rad   ). Load initially with the torque of the shaft ) . ( 50 m N TL  , then at time t = 4.5(s) and t = 5.5(s), we increase L T to 100 (N.m) and 200 (N.m). The simulation results are shown in Figure 6(a). The simulation results show that the change of speed values meet very good requirements. For clarity, we study in more detail the graph of the set speed and actual speed in Figure (6b). From the graph (6b), we see that the actual speed value is very close to the set speed value. The change in speed depends on the load is shown in Figure (6c). Simulation results show that the system is very high quality, the speed of the Motor is almost unchanged when the torque changes. From the results above, we see that the proposed method with the simple control algorithm has the high efficiency. Figure 6. The simulated results with the flatness controller
  • 6. IJPEDS ISSN: 2088-8694  The Control Structure for DC Motor based on the Flatness Control (Thang Nguyen Trong) 1819 3. THE PROBLEM OF THE PARAMETER ERROR OF THE MOTOR MODEL The simulation results in part 2 show that the quality of the control system is perfect, because of the assume that we know exactly the parameters of the DC Motor. However, in reality, it is impossible to know the parameters of DC exactly, so the quality of control system is not perfect as above. To check the control quality when DC parameter is not known exactly, we assume that some parameters of the DC Motor are changed, the parameter of the DC Motor, after changed is shown in Table 2: Table 2. The parameters of DC Motor after changed Ra() La(H) Rf() Lf(H) Laf(H) J(kg.m^2) Bm(N.m.s) Tf(N.m) 0.55 0.016 220 145 1.6 1.3 0.6 20 Running the system model, the response of the actual speed and set speed is shown in Figure 7. The results show that there is a difference between the set speed and the actual speed. To eliminate this difference, we add a PID controller connected in parallel with the flatness controller. The parallel control diagram is shown in Figure 8. The simulation model with the additional PID controller is shown in Figure 9. Figure 7. The simulated results when the DC parameter is not known exactly Figure 8. The parallel control diagram
  • 7.  ISSN: 2088-8694 IJPEDS Vol. 8, No. 4, December 2017 : 1814 – 1821 1820 Figure 9. The simulation diagram of the control system with the additional PID controller Running the model with the additional PID controller and Kp=3, Ki=0.5, the simulation results are shown in Figure 10. The results show that when changing the set speed, the actual speed of DC Motor is very close to the set speed, and when the torque of the shaft changes, the speed of DC Motor is not affected much. So the flatness control system for DC Motor with the support of the PID controller has worked very well. Figure 10. The simulated results with the additional PID controller 4. CONCLUSION In this paper, the author has successfully built the control system for DC Motor based on a flatness control. The simulation results demonstrate that the system with the flatness controller works very well if we know exactly the parameters of DC Motor. However, in fact, the parameters of the DC Motor have not known accurately, so there is the error between set speed and actual speed when only the flatness control is applied. A PID controller has been put into operation in parallel with the flat controller to eliminate their error. The simulation results show that the quality of the whole system is very good and work effectively. The actual speed of DC Motor is very close to the desired speed with the small transaction time. More, if the load or the torque of the DC motor shaft is changed but the rotor speed of DC motor is not affected much. Thus, the proposed system can be applied well in motion control applications that require the high-quality of the speed control. REFERENCES [1] Abdelhak, B., & Bachir, B., “A High gain observer based sensorless nonlinear control of induction machine,” International Journal of Power Electronics and Drive Systems, 5(3), 305, 2015.
  • 8. IJPEDS ISSN: 2088-8694  The Control Structure for DC Motor based on the Flatness Control (Thang Nguyen Trong) 1821 [2] Gunabalan, R., & Subbiah, V., “Speed Sensorless Vector Control of Induction Motor Drive with PI and Fuzzy Controller,” International Journal of Power Electronics and Drive Systems, 5(3), 315, 2015. [3] Park, J. S., & Lee, K. D., “Design and Implementation of BLDC Motor with Integrated Drive Circuit,” International Journal of Power Electronics and Drive Systems (IJPEDS), 8(3), 1109-1116, 2017. [4] Hughes, Austin, and Bill Drury, “Electric Motors and drives: fundamentals, types and applications,” Newnes, 2013. [5] Shieh, N. C., and P. C. Tung, "Robust output tracking control of a linear DC brushless Motor for transportation in manufacturing system", IEE Proceedings-Electric Power Applications, 2001,pp. 119-124. [6] Pickrell, Don, and Paul Schimek, "Growth in Motor vehicle ownership and use: Evidence from the Nationwide Personal Transportation Survey", Journal of Transportation and Statistics, vol.2.1, pp.1-17, 1999. [7] Fletcher, David I., and John H. Beynon, "Development of a machine for closely controlled rolling contact fatigue and wear testing", Journal of testing and evaluation, Vol 28.4, pp. 267-275, 2000. [8] Bosco, Maycon Chimini, et al, "Estimation of parameters and tuning of a speed PI of permanent magnet DC Motor using differential evolution", Electric Machines and Drives Conference (IEMDC), IEEE International,2017,pp.1-6. [9] Yao, Jianyong, Zongxia Jiao, and Dawei Ma, "Adaptive robust control of DC Motors with extended state observer", IEEE Transactions on Industrial Electronics Vol 61.7 ,2014, pp. 3630-3637. [10] Xue, Dingyu, Chunna Zhao, and YangQuan Chen, "Fractional order PID control of a DC-Motor with elastic shaft: a case study", American Control Conference, IEEE, 2006, pp.1-6 [11] Thomas, Neenu, and Dr P. Poongodi, "Position control of DC Motor using genetic algorithm based PID controller", Proceedings of the World Congress on Engineering, 2009, vol. 2, pp. 1-3. [12] Yazdanpanah, R., Soltani, J., & Markadeh, G. A., “Nonlinear torque and stator flux controller for induction motor drive based on adaptive input–output feedback linearization and sliding mode control”, Energy Conversion and management, 49(4), 541-550, 2008. [13] Abdelmadjid, G., Seghir, B. M., Ahmed, S., & Youcef, M., “Sensorless sliding mode vector control of induction motor drives,” International Journal of Power Electronics and Drive Systems, 2(3), 277, 2012. [14] Trabelsi, R., Khedher, A., Mimouni, M. F., & M'sahli, F., “Backstepping control for an induction motor using an adaptive sliding rotor-flux observer,” Electric Power Systems Research, 93, 1-15, 2012. [15] Martin, P., Murray, R. M., & Rouchon, P., “Flat systems, equivalence and trajectory generation,” 2003. [16] Xian-lin, C. H. E. N, "Flatness control in new generation high-tech mills for wide strip rolling", Journal of University of Science and Technology Beijing, Vol 19, pp.1-5, 1997. [17] Jelali, Mohieddine, "Performance assessment of control systems in rolling mills–application to strip thickness and flatness control", Journal of Process Control, Vol 17.10,pp. 805-816, 2007. [18] Farid, B., Waffa, B., & Bachir, B. A., “Flatness Based Nonlinear Sensorless Control of Induction Motor Systems,” International Journal of Power Electronics and Drive Systems, 7(1), 265, 2016. [19] Delaleau, Emmanuel, and Aleksandar M. Stankovic, "Flatness-based hierarchical control of the PM synchronous Motor", American Control Conference, Proceedings, Vol. 1, IEEE, 2004, pp. 65-70. BIOGRAPHY OF AUTHOR Thang Nguyen Trong received the B.Eng.degree in Automation Control from Hanoi University of Science and Technology in 2005, and Ph.D.degrees in Control Engineering and Automation from University of Transport and Communications, Vietnam in 2014. He is currently the Head of Department of Industrial Electrical Engineering and Automation, Haiphong Privite University, Vietnam. He is a member of Instittute of Electrical and Electronic Engineers (IEEE), his research interests include automattion control theory, electric drive control, power generation systems on ships.