A CMAC Based Self-Tuning Intelligent PID Controller for Electric Load Simulator

Author

Han Huatao ; Yang Bo

Author_Institution

Sch. of Autom. Sci. & Electr. Eng., Beihang Univ., Beijing, China

fYear

2013

fDate

21-23 Sept. 2013

Firstpage

1443

Lastpage

1448

Abstract

With the advantages of quick learning, simple structure, nonexistent local optimum and good real-time performance, the Cerebella Model Articulation Controller (CMAC) has been widely used in the control of nonlinear systems. In this paper, the genetic algorithm is used to identify uncertain parameters of electric load simulator to improve the credibility of the mathematical model. Then a CMAC-based self-tuning intelligent PID controller is proposed for electric load simulators. The simulation and experimental results demonstrate that the proposed intelligent PID controller has good robustness and can effectively eliminate the surplus torque with high control precision.

Keywords

cerebellar model arithmetic computers; control nonlinearities; control system analysis; genetic algorithms; intelligent control; nonlinear systems; self-adjusting systems; three-term control; torque; CMAC; cerebella model articulation controller; control precision; electric load simulator; genetic algorithm; mathematical model; nonlinear systems; self-tuning intelligent PID controller; surplus torque elimination; Brushless DC motors; Load modeling; Loading; Mathematical model; Torque; Cerebellar Model Articulation Controller (CMAC); Electric load simulator; Parameter identification; Self-tuning PID controller;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation, Measurement, Computer, Communication and Control (IMCCC), 2013 Third International Conference on

Conference_Location

Shenyang

Type

conf

DOI

10.1109/IMCCC.2013.322

Filename

6840712