Speed control of DC motor using conventional and adaptive PID controllers

Proportional Integral Derivative (PID) controllers are extensively used in practical industries to control the speed of DC Motors. The single weakness of PID controllers is their sensitivity to variation in parameters and operating conditions; thus, tuning the controller gains to adapt with these variations presents a practical challenge. In this paper, an adaptive mechanism that utilizes a Recursive Least Square (RLS) algorithm, with rate limiters, is implemented to perform an online self-adjusting of each of the PID gains in order to achieve Adaptive PID (APID) controller that will accommodate to system variations. MATLAB/ Simulink software is used to implement and simulate APID control of a Chopper-Fed DC motor. A conventional PID control system is also designed and simulated to obtain results that can be used to judge the performance of the APID controller. Results proved that the APID controller forced the motor speed to track the reference input with insignificant tracking error, and also managed to attain the motor speed at its desired value, regardless of the load changes inflected on the motor. This enhances both transient and steady-state speed responses.

[1]  Fredy E. Hoyos,et al.  Controlling a DC Motor through Lypaunov-like Functions and SAB Technique , 2018, International Journal of Electrical and Computer Engineering (IJECE).

[2]  Singari v.s.r. Pavankumar,et al.  A Neuro-fuzzy Based Speed Control of Separately Excited DC Motor , 2010, 2010 International Conference on Computational Intelligence and Communication Networks.

[3]  Byamakesh Nayak,et al.  Parameter estimation of DC motor through whale optimization algorithm , 2019, International Journal of Power Electronics and Drive Systems (IJPEDS).

[4]  G. G RajaSekhar,et al.  Solar PV fed non-isolated DC-DC converter for BLDC motor drive with speed control , 2019 .

[5]  Feri Yusivar,et al.  Design and implementation of adaptive PID controller for speed control of DC motor , 2017, 2017 15th International Conference on Quality in Research (QiR) : International Symposium on Electrical and Computer Engineering.

[6]  C. C. Chan Low-Cost Electronic-Controlled Variable-Speed Reluctance Motors , 1987, IEEE Transactions on Industrial Electronics.

[7]  S. Naveen,et al.  Chopper Fed Speed Control of DC Motor Using PI Controller , 2016 .

[8]  Chong Chen,et al.  Self-tuning PID Control of Induction Motor Speed Control System Based on Diagonal Recurrent Neural Network , 2015 .

[9]  J. N. Nderu,et al.  Adaptive PID Dc Motor Speed Controller With Parameters Optimized with Hybrid Optimization Strategy , 2011 .

[10]  Rania A. Fahmy,et al.  Adaptive PID Controller Using RLS for SISO Stable and Unstable Systems , 2014 .

[11]  Liangtao Zhu Adaptive control of sinusoidal brushless DC motor actuators. , 2011 .

[12]  Masaru Uchiyama,et al.  Neural Network Based Tuning Algorithm for MPID Control , 2011 .

[13]  Sangeeta D. Jain,et al.  Speed control of Separately Excited DC Motor using various Conventional Controllers , 2015 .

[14]  Ameer L. Saleh,et al.  Resolving of optimal fractional PID controller for DC motor drive based on anti-windup by invasive weed optimization technique , 2019, Indonesian Journal of Electrical Engineering and Computer Science.

[15]  Waleed I. Hameed,et al.  SPEED CONTROL OF SEPARATELY EXCITED DC MOTOR USING FUZZY NEURAL MODEL REFERENCE CONTROLLER , 2012 .

[16]  N. S. Sultan,et al.  Optimal PID controller of a brushless dc motor using genetic algorithm , 2019, International Journal of Power Electronics and Drive Systems (IJPEDS).

[17]  Moleykutty George,et al.  Speed Control of Separately Excited DC Motor , 2008 .