Genetic algorithm tuning of Lyapunov-based controllers: an application to a single-link flexible robot system

Abstract

In this paper, a systematic controller design approach is proposed to guarantee both closed-loop stability and desired performance of the overall system by effectively combining genetic algorithms (GAs) with Lyapunov's direct-controller design method. The effectiveness of the approach is shown by using a simple and efficient decimal GA optimization procedure to tune and optimize the performance of a Lyapunov-based robust controller for a single-link flexible robot. The feedback gains of the controller are tuned by the GA optimization process to achieve good results for tip motion control of the single-link flexible robot based on some suitable fitness functions. The paper includes results of simulation experiments demonstrating the effectiveness of the proposed genetic algorithm approach.