Design and robustness enhancement of sectorial fuzzy controller via evolutionary algorithm

Abstract

This paper presents an evolution search methodology to automatically design a sectorial fuzzy controller (SFC). The evolution search methodology is an integer-coded evolutionary algorithm (EA) which involves two stages. At first stage, the proposed EA optimises the SFC for disturbance-free model of the plant to be controlled. The principal aim of the second stage is the robustness enhancement of the evolved SFC resulting from the former stage. Specifically, the proposed EA looks in the vicinity of the best SFC found in the first stage for a SFC that provide the best compromise between the control performance for a disturbance-free model and for disturbed model. The sectorial properties were accommodated in the evolutionary search through a special parameterization of the fuzzy rule base (FRB) and the membership functions (MFs) of the SFC, repairing operator and special initialization of FRB chromosome part. Simulations were performed for direct-drive DC motor. The evolved SFC with the proposed design methodology found to provide very satisfactory performance under different types of disturbances. The trade-off between the accuracy performance and the robustness performance is also analysed during the evolution process.