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

fYear

2011

fDate

16-18 Sept. 2011

Firstpage

1950

Lastpage

1953

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Control Engineering (ICECE), 2011 International Conference on

Conference_Location

Yichang

Print_ISBN

978-1-4244-8162-0

Type

conf

DOI

10.1109/ICECENG.2011.6057865

Filename

6057865