Auto Tuning of Fuzzy PI Type Controller Using Fuzzy Logic
Saurabh Chopra, Rudrajit Mitra, Vijay Kumar · 2008
Abstract — In this paper, a simple and effective method for tuning of fuzzy PI (proportional-integral) controller based on fuzzy logic is proposed. Here the input scaling factors are tuned online by gain updating factors whose values are determined by rule base with the error and change in error as inputs according to the required controlled process. The rules are designed for tuning the scaling factors based on the performance measures such as peak overshoot (OV), Rise time (RT) and Amplitude (AM). The performance comparison of conventional FLC with auto tuned fuzzy PI type controllers has been done in terms of several performance measures such as peak overshoot, settling time and rise time and integral square error (ISE). In addition to the responses due to step set-point change, a random noise is also added in some systems. Simulation results show the effectiveness and robustness of the proposed auto tuning mechanism. Furthermore, a clustering method is used to reduce the fuzzy inference rules of the three fuzzy reasoning blocks which reduces the computational time and memory. The clustering based Fuzzy Logic Controllers is compared with those of conventional Fuzzy Logic Controllers in both cases (with and without tuning). A simulation analysis of a wide range of linear and nonlinear processes is carried out and comparison of results shows computational time and memory is reduced to a great