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- Authors : Sunil Yadav, Santosh Kumar
- Paper ID : IJERTV7IS120078
- Volume & Issue : Volume 07, Issue 12 (December – 2018)
- Published (First Online): 05-01-2019
- ISSN (Online) : 2278-0181
- Publisher Name : IJERT
- License: This work is licensed under a Creative Commons Attribution 4.0 International License
Design & Simulation of Speed Control for DC Drives using Smart Controller
Design & Simulation of Speed Control for DC Drives using Smart Controller
Sunil Yadav1, Santosh Kumar2
Department of Electrical & Electronics Engineering Millennium Institute Technology & Science, Bhopal (MP) 462044,
Abstract– This paper presents a hybrid PID-MRAC control system for the speed control of a DC motor. The proposed method incorporates PID and MARC controllers with utilization of Gradient Descent method & control technique. This method combines the advantages of PID controller and MARC controllers to improve the speed response of the DC motor. Simulation & modeling of DC Motor and Speed control for DC Motor using Smart Controller (PID Controller and MRAC) was done. The mathematical model of DC motor with independent armature/filed control can be obtained by considering the electrical system, electromagnetic interaction and mechanical system. Simulation models for DC motor speed control methods and feedback control system using DC motor drives have been developed with Model Reference Adaptive Control in Simulink/Matlab using Gradient Descent method. Model Reference Adaptive Control method is implanted in Modeling of armature voltage control DC motor to find the results of speed v/s time to stimulate discrete model and also simulate the DC Motor model and DC Motor Model with PID Controller
Index: – DC Motor, Existing tuning, MRAC, Steady State Error, PID controller, Simulink, MATLAB
During the nineteenth century, when power supply was dc, dc motors were used extensively to draw power direct from the dc source. The advent of thyristors capable of handling large current has revolutionized the field of electric power Control. DC motor drives are used for many speed and position control systems where their excellent performance, ease of control and high efficiency are desirable characteristics.
DC motor are generally controlled by conventional Proportional Integral Derivative (PID) controllers, since they designed easily, have low cost, inexpensive maintenance and effectiveness. It is necessary to know systems mathematical model or to make some experiments for tuning PID parameters. Due to its excellent speed control characteristics, the DC motor has been widely used in industry even though its maintenance costs are higher than the induction motor. As a result, position control of DC motor has attracted considerable research and several methods have evolved. Proportional-Integral Derivative (PID) controllers have been widely used for speed and position control of DC motor.
Automation control, motion control and machine automation systems are used to improve manufacturing performance and flexibility. Engineering assistance with machine safety, energy efficiency, and breakthrough motion control and automation concepts. Reduce energy consumption. Improve worker safety. Make more effective
use of new, integrated approaches to complex engineering challenges.
Computer modeling and simulation tools have been extensively used to support and enhance electric machinery courses. MATLAB with its toolboxes such as Simulink  and Sim Power Systems .Traditionally rheostatic armature control method was widely used for the speed control of low power DC motors. The desired torque-speed characteristics could be achieved by the use of hybrid conventional proportional-integral-derivative (PID) and MRAC controllers.
DC MOTOR MODEL
The resistance of the field winding and its inductance of the motor used in this study are represented by Rf and Lf, respectively. The resistance of the armature and its inductance are shown by Ra and La respectively in dynamic model. Armature reaction effects are ignored in the description of the motor. This negligence is justifiable to minimize the effects of armature reaction since the motor used has either interlopes or compensating winding. The fixed voltage Vf is applied to the field and the field current settles down to a constant value. A linear model of a simple DC motor consists of a mechanical equation and electrical equation as determined in the following equations
From the above three equations we can get in S domain equation (4) as given below
Put all parameters values in equation no. (4) as shown in just above
Ra = 2.45 ohm La = 0.035 H
Kb = 1.2 volt/ (rad/sec)
J = 0.022Kg-m^Â²/rad
B = 0.5*10^Â³ N-m/ (rad/sec)
controller input (D controller), increase in control signal to
0.00077 s 3
lead error towards zero (I controller) and suitable action
inside control error area to eliminate oscillations (P
Simulation of transfer function of equation (4)
Fig.1: Simulink Model of DC Motor Uing Transfer Function
Fig.2: Simulink Model of DC Motor Transfer Function of equation (4)
SPEED CONTROL OF DC MOTOR
The DC motor can be controlled by controlling armature voltage and armature current. We know that speed control is possible by varying
Flux per pole (controlling of flux).
Resistance Ra of armature (By Rheostat Control).
The above methods have some demerits like a large amount of power is dissipate in the controller resistance hence efficiency decreased. And also it requires very complicated and expensive arrangement for dissipations of heat produced in the controller resistance. It also gives very low speed below the normal speed. So by this we can conclude that these electrical and electromechanical methods are less economical, efficient and not of much use
controller). Derivative mode improves stability of the system and enables increase in gain Kp, which increases speed of the controller response. The output of PID controller consists of three terms the error signal, the error integral and the error derivative. Fig.3 shows the block diagram of PID controller. PID controller combines the advantage of proportional, derivative and integral control action.
Fig.3 PID controller block diagram.
Table1: The effects of gain coefficients on the performance of PID controller system.
Steady State Error
V. SPEED CONTROL WITH MRAC
Model reference adaptive control (MRAC) is one of the main approaches to adaptive control. The basic structure of a MRAC scheme is shown in Fig. 4. The reference model is chosen to generate the desired
as these methods are having multiple drawbacks, so
ym that the plant output,
yp has to follow. The
electronic methods and techniques are used for controlling of speed. These methods provide higher efficiency and
e yp ym
represents the deviation of
feasibility, good reliability and quick response. One such very widely used technique is smart controller which the
the plant output from the desired trajectory. The closed-
loop plant is made p of an ordinary feedback control law
combination of PID controller and MRAC controller. We
that contains the plant and a controller
apply this technique in our work to control the speed of DC motor.
SPEED CONTROL WITH PID CONTROLLER Proportional-Integral-Derivative, PID, controller is
widely used in industrial control system. PID controller has all the necessary dynamics: fast reaction on change of the
adjustment mechanism that generates the controller parameter estimates (t) on the line. This design
methodology allows the use of a wide class of adaptive algorithms that includes gradient, least-squares and those based on the SPR Lyapunov design approach
Fig.4: DC drive with model referencing adaptive speed control Scheme
DESIGNED MODEL FOR DC MOTOR SPEED
The Simulink model used to get desired speed characteristic for a DC Motor is shown in fig.5. This system (plant) under control is a continuous-time system. The heart of the controller is a PID. The problem of realizing this system is mainly one of simulating dc motor with the help of its transfer function equations as shown in above.
Fig.5: Simulink model of DC motor with controllers
This section discussed the results generated with different condition of load applications for the validation of work. Here Simulation results of speed control of DC motor using controller are shown in figure nos. 6 to 9.
Fig.6: Simulink model of DC motor Transfer Function
Fig.7:Simulink Result of DC Moter Transfer Function Armature Curent
Fig.8: Simulink Result of DC Moter with PID Controller
Fig.9: Simulink Model of DC Moter with PID in MRAC method
The speed of a dc motor has been successfully controlled by using smart Controller. A generalized modeling of dc motor is done. After that a complete layout of DC drive system is obtained. A DC motor specification is taken and corresponding parameters are found out from derived design approach. The effect of armature voltages, resistance, inductance and reaction on controlling of speed characteristic is observed. Ultimately simulation is done for model. The simulation speed/time plots show that, before steady state conditions are reached, the following occurs.
The speed takes a certain time to initially reach the level of the final value (the rise time).
The speed overshoots the level of the final value.
The speed oscillates about the level of the final value.
The speed control of DC motor by modern adaptive control method is achieved.
REFERENCES Dubey, G.K., Fundamentals of Electrical Drives. New Delhi, Narosa Publishing House, 2009.  Gopal, M., Control Systems, Principles and Design. New Delhi, Tata McGraw Hill Publishing Company limited 2008.  Wood, A.J. and B.F. Wallenberg, (2007) Power Generation, Operation, and Control, 2nd ed., Wiley India (P.) Ltd., 4435/7, Ansari Road, Daryaganj, New Delhi 110 002, India, Chapter 9, pp. 328-360.  H. Bevrani, (2009) Robust Power System Frequency Control, Springer Science + Business Media, LLC, 233 Spring Street, New York, NY-10013, USA, Chapter 2, pp.15-30.  B.J. Chalmers, Influence of saturation in brushless permanent magnet drives. IEEE proc. B, Electric Power Apply, vol.139, no.1, 2015.  C.T. Johnson and R.D. Lorenz, Experimental identification of friction and its compensation in precise, position controlled mechanism. IEEE Trans. Ind, Applicant, vol.28, no.6, 2010.  J. Zhang, N. Wang and S. Wang, A developed method of tuning PID controllers with fuzzy rules for integrating process, Proceedings of the American Control Conference, Boston, 2004, pp.1109-1114.  K.H. Ang, G. Chong and Y. Li, PID control system analysis, design and technology, IEEE transaction on Control System Technology,
Vol.13, No.4, 2005, pp. 559-576 H. X. Li and S.K. Tso, "Quantitative design and analysis of Fuzzy Proportional-Integral-Derivative Control- a Step towards Auto tuning", International journal of system science, Vol.31, No.5, 2000, pp.545-553.  Nitin Goel, P. R. Sharma, and Suman Bala, "PERFORMANCE ANALYSIS OF SPWM INVERTER FED 3-PHASE INDUCTION MOTOR DRIVE USING MATLABSIMULINK," International
Journal of Advanced Technology in Engineering and Science, vol. 2, no. 6, pp. 183-193, June 2014. Felix Jauch and JÃ¼rgen Biela, Speed Control of DC Motor Using PID & Smart Controller, IEEE Transactions on Power, Volume: 31 Issue: 12, 2016.  Sin-Woo Lee and Hyun-Lark Do, Self-organizing Adaptive Fuzzy Controller. Fuzzy set and systems, IEEE Transactions on Industries Volume: 63 Issue: 10 . 2015.  Purushotam Kumar, Prabhakar Kumar Prabhat, Mithun Kumar, Dr.
S.D. Choudhary , Speed Control of DC Motor Using PID & Fuzzy Controller, International Journal of Scientific & Engineering Research, Volume5, Issue11, November-2014, 1044, ISSN 2229- 5518. Shashi Bhushan Kumar & "et al.", Design and Simulation of Speed Control of DC Motor by Artificial Neural Network Technique , International Journal of Scientific Research & Publications, Volume 4, Issue 7, July 2014, ISSN 2250-3153.  Akie Uehara & "et.", A Fuzzy-Logic Based Output Power Smoothing Method of WECS with PMSG using Inertia of Wind Turbine , JICEE Vol. 1, No. 3, pp. 309~316, 2011.  Wood, A.J. and B.F.Wollenberg, Power Generation, Operation, and Control, 2nd ed., Wiley India (P.) Ltd. 2007, Chapter 9, pp. 328- 360.  Ashok Kusagur, Shankarappa Fakirappa Kodad, and Sanker Ram, "Modelling & Simulation of an ANFIS controller for an AC drive," World Journal of Modelling and Simulation, vol. 8, no. 1, pp. 36-49, March 2011.  Ch Chengaiah and Silva Prasad, "Performance of Inductoin Motor Drive by Indirect vector controlled method using PI and Duzzy Controllers," International Journal of Science, Environment, vol. 2, no. 3, pp. 475-469, 2013.