Abstract
Despite the demonstrated effectiveness of fuzzy logic controllers in linear and nonlinear systems, the major limitation is that there exists a steady-state error. This work presents a novel single input PID-type fuzzy logic controller that minimizes the steady-state error. It adopts the function of the error, derivative of the error, and the integral of the error to produce a single input variable of the single input fuzzy logic controller. Controller parameters are then optimized by multiobjective genetic algorithm. The proposed framework was tested on a system that has a third-order transfer function and on a permanent magnet linear synchronous motor system. The proposed framework has obtained good performance in minimizing the steady-state error. Additionally, there are only three rules required.
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