Title :
Adaptive PID regulator based on neural network for DC motor speed control
Author :
Zhang, Shumei ; Zhou, Xiang ; Yang, Liu
Author_Institution :
Inst. of Automotive Electron. Technol., Shanghai Jiao Tong Univ., Shanghai, China
Abstract :
This paper investigates the use of an adaptive PID controller to reduce a DC motor speed pulsation such that the robust stability for the closed-loop system is guaranteed. .The APID control scheme tunes the PID controller parameters by using the theory of adaptive interaction. A neural network was applied in the adaptive algorithm to regulate a set of PID parameters by minimizing an error function.Both computer simulations and bench test rig experiments are used to validate the proposed control scheme.
Keywords :
DC motors; adaptive control; angular velocity control; closed loop systems; machine control; neurocontrollers; robust control; three-term control; APID control scheme; DC motor speed control; DC motor speed pulsation reduction; adaptive PID regulator; adaptive algorithm; adaptive interaction theory; closed-loop system; error function minimization; neural network; robust stability; Decision support systems; DC motor closed-loop system adaptive algorithm error function; PID controller;
Conference_Titel :
Electrical and Control Engineering (ICECE), 2011 International Conference on
Conference_Location :
Yichang
Print_ISBN :
978-1-4244-8162-0
DOI :
10.1109/ICECENG.2011.6057865
