Title :
A GA-optimized fuzzy PD+I controller for nonlinear systems
Author :
Tang, K.S. ; Man, Kim F. ; Chen, Guanrong ; Kwong, Sam
Author_Institution :
Dept. of Electron. Eng., City Univ. of Hong Kong, Kowloon, China
Abstract :
This paper presents a design and simulation study of a fuzzy PD+I controller optimized via a multi-objective genetic algorithm (MOGA). The fuzzy PD+I controller preserves the linear structure of the conventional PID controller but has self-tuned gains. The proportional, integral and derivative gains are nonlinear functions of their input signals, which have a certain adaptive capability in set-point tracking performance. The proposed design is then optimized by using the MOGA. It is tested with a couple of simulated nonlinear systems, which demonstrate that these optimized gains make the fuzzy PD+I controller robust, with a faster response time and less overshoot than its conventional and non-optimized counterparts
Keywords :
adaptive control; control system analysis; control system synthesis; fuzzy control; genetic algorithms; nonlinear control systems; optimal control; performance index; robust control; self-adjusting systems; simulation; three-term control; tracking; MOGA; PID controller; adaptive capability; controller design optimization; derivative gain; fuzzy PD+I controller; input signals; integral gain; linear structure; multi-objective genetic algorithm; nonlinear functions; nonlinear systems control; overshoot; proportional gain; response time; robust controller; self-tuned gains; set-point tracking performance; simulation; Algorithm design and analysis; Control systems; Design optimization; Fuzzy control; Fuzzy systems; Genetic algorithms; Nonlinear control systems; Nonlinear systems; Performance gain; Three-term control;
Conference_Titel :
Industrial Electronics Society, 2001. IECON '01. The 27th Annual Conference of the IEEE
Conference_Location :
Denver, CO
Print_ISBN :
0-7803-7108-9
DOI :
10.1109/IECON.2001.976703
