Abstract

A novel tuning method is proposed for the design of fuzzy PID controllers for multivariable sys- tems. In the proposed method, a PID controller is expressed in terms of fuzzy rules, in which the input variables are the error signals and their derivatives, while the output variables are the PID gains. In this manner, the PID gains are adaptive and the fuzzy PID controller has more flexibility and capability than con- ventional versions with fixed gains. A particle swarm optimization (PSO) method is proposed for tuning of the fuzzy PID controller, in which the centers and the widths of the Gaussian membership functions, the num- ber of fuzzy control rules, and the PID gains are all parameters to be determined simultaneously. Meanwhile, based on the concept of multiobjective optimization, ways of defining the fitness function of the PSO to in- clude different performance criteria are also discussed. To show the feasibility and validity of the resulting fuzzy PID controller, illustrative experimental results for a multivariable seesaw system are included.

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