Optimization of sliding mode controller for double inverted pendulum based on genetic algorithm

Abstract

The double inverted pendulum system is a less-driven, multi-parameter, highly nonlinear system. The sliding mode controller is designed to make the double pendulum stable at the upright equilibrium position. But, it is difficult to determine the sliding surface in design, which is the key to the performance of the control system. The improved genetic strategy is applied to search the optimal sliding surface and other important parameters. The improved genetic strategy effectively improves the ability of the global convergence and local search capabilities, enhancing the diversity of the population and avoiding the premature convergence. Simulation experiment shows that the sliding mode controller optimized by the improved genetic algorithm stabilizes the double inverted pendulum with satisfied performance.