Sliding Mode Controller for Nonlinear System Based on Genetic Algorithm

Abstract

Sliding Mode Controller (SMC) is a simple and effective method to recognize a robust controller for nonlinear system. It is a strong mathematical tool which gives a nonlinear robust controller with acceptable performance. The chattering phenomenon is the major drawback that sliding mode control suffers from. This phenomenon causes a zigzag motion along the sliding surface. In this work to design SMC, the Saturation function (i.e., boundary layer) has been used instead of the Sign function that was used in classical sliding mode controller in order to reduce the chattering phenomena which are appearing in the sliding mode phase. The genetic algorithms have also been proposed in this work for the parameter selection method of Sliding Mode Controller and the results showed a high speed of the system state for reaching the sliding surface during the reaching phase and a chattering reduction during the sliding phase. A pendulum system has been used for testing the designed sliding mode controller. The simulation results showed good validity of the suggested method. Matlab programming and simulink were adopted for the simulation results.