Automatic rule tuning of a fuzzy logic controller using particle swarm optimisation

Authors:
Gu Fang;Ngai Ming Kwok;Dalong Wang
Affiliations:
School of Engineering, University of Western Sydney, Penrith South, Australia;School of Mechanical & Manufacturing Engineering, University of New South Wales, Sydney, NSW, Australia;School of Mechanical & Manufacturing Engineering, University of New South Wales, Sydney, NSW, Australia
Venue:
AICI'10 Proceedings of the 2010 international conference on Artificial intelligence and computational intelligence: Part II
Year:
2010

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Abstract

While fuzzy logic controllers (FLCs) are developed to exploit human expert knowledge in designing control systems, the actual establishment of fuzzy rules and tuning of fuzzy membership functions are usually a time consuming exercise. In this paper a technique, based on the particle swarm optimisation (PSO), is employed to automatically tune the fuzzy rules of a Mamdani-type of fuzzy controller. The effectiveness of the designed controller is demonstrated by the control performance of such an FLC to a nonlinear water tank system with process time delay. The results are compared favourably to a PSO tuned PID controller.