Sliding mode controller with sliding perturbation observer based on gain optimization using genetic algorithm

Abstract

This paper proposes a new robust motion control algorithm. The algorithm uses partial state feedback for a class of nonlinear systems with modeling uncertainties and external disturbances. The major contribution is to design a robust observer for the state and the perturbation of the Stewart platform, which is combined with a variable structure controller (VSC). The combination of controller and observer provides the robust routine called sliding mode control with sliding perturbation observer (SMCSPO). The optimal gains of SMCSPO, determined by nominal eigenvalues are easily obtained by genetic algorithm. The proposed fitness function to optimize the gain is defined using the sliding function. The control performance of the proposed algorithm is found to be satisfactory based on the simulation and experiment with Stewart platform.