TY - JOUR

T1 - MRAS Based Speed Control of DC Motor with Conventional PI Control — A Comparative Study

AU - Sachit, Sariga

AU - Vinod, B. R.

N1 - Publisher Copyright: © 2022, ICROS, KIEE and Springer.

PY - 2022/1

Y1 - 2022/1

N2 - The major challenges in applying a conventional speed controller in DC motor are the effects of motor non-linearity. The non-linear characteristics of a DC motor like, saturation and friction could degrade the performance of conventional controllers. The parameters of such a dynamic system changes with time and drive the system beyond the stability margins. The conventional feedback control system thereby fails to maintain the control especially when the plant parameters are unknown. To overcome these problems, an adaptive control system is proposed which can cope up with the changes in motor dynamics. The control scheme used here is the model reference adaptive system (MRAS) where the output of the unknown plant is tuned to track the output of the ideal reference model. The perfect adaptation is achieved by an adaptive estimator implemented based on MIT rule. The plant output is stabilized by an auto-PID controller (PID controller that tunes its parameters by its own) along with the adaptive estimator. The adaptation mechanism modulates the controller and update the controller parameters to minimize error and track the ideal output. The entire proposed system is modelled and simulated in MATLAB, SIMULINK. The results are analyzed and compared over conventional PI control scheme as a part of the study. The proposed system showed better resistance to the forced perturbations induced, with good decay ratio and fine settling. The system showed satisfactory results when operated in low, medium and high speeds. The motive of the thesis is to implement a self-adaptive and autonomous DC motor speed control for variable orbit tracking applications in robotics, launch vehicles, space probes, satellites, unmanned rovers etc.

AB - The major challenges in applying a conventional speed controller in DC motor are the effects of motor non-linearity. The non-linear characteristics of a DC motor like, saturation and friction could degrade the performance of conventional controllers. The parameters of such a dynamic system changes with time and drive the system beyond the stability margins. The conventional feedback control system thereby fails to maintain the control especially when the plant parameters are unknown. To overcome these problems, an adaptive control system is proposed which can cope up with the changes in motor dynamics. The control scheme used here is the model reference adaptive system (MRAS) where the output of the unknown plant is tuned to track the output of the ideal reference model. The perfect adaptation is achieved by an adaptive estimator implemented based on MIT rule. The plant output is stabilized by an auto-PID controller (PID controller that tunes its parameters by its own) along with the adaptive estimator. The adaptation mechanism modulates the controller and update the controller parameters to minimize error and track the ideal output. The entire proposed system is modelled and simulated in MATLAB, SIMULINK. The results are analyzed and compared over conventional PI control scheme as a part of the study. The proposed system showed better resistance to the forced perturbations induced, with good decay ratio and fine settling. The system showed satisfactory results when operated in low, medium and high speeds. The motive of the thesis is to implement a self-adaptive and autonomous DC motor speed control for variable orbit tracking applications in robotics, launch vehicles, space probes, satellites, unmanned rovers etc.

KW - Adaptive control

KW - DC Motor

KW - MIT rule

KW - MRAS

KW - PI controller

UR - http://www.scopus.com/inward/record.url?scp=85123030069&partnerID=8YFLogxK

U2 - 10.1007/s12555-020-0470-1

DO - 10.1007/s12555-020-0470-1

M3 - Article

AN - SCOPUS:85123030069

VL - 20

SP - 1

EP - 12

JO - International Journal of Control, Automation and Systems

JF - International Journal of Control, Automation and Systems

SN - 1598-6446

IS - 1

ER -