Automatic Fuzzy Membership Function Tuning Using the Particle Swarm Optimization

Fuzzy logic controllers (FLCs) are developed to exploit human expert knowledge in designing control systems.  While the fuzzy rules are relatively easy to obtain, fuzzy membership function (MF) tuning could be a time consuming exercise.  In this paper the particle swarm optimization technique is employed to automatically tune the MFs of a Mamdani-type of fuzzy controller. The effectiveness of the proposed controller is demonstrated by the control performance of such an FLC of a nonlinear water tank system. The results are compared favourably to a PSO tuned PID controller.