Controller parameters optimization of large inertia and time-varying load system based on extremum seeking algorithm

It is difficult to tune controller parameters for large inertia and time-varying load system. To solve this problem, a new controller parameters optimization strategy based on extremum seeking algorithm is proposed. This novel method is model-free. It utilizes data of experiments to get the gradient information of performance to control parameters, so as to tune the controller parameters. This paper analyzes the convergence of extremum seeking algorithm and proposes the high-pass filter parameters selection principles. Simulation and experimental results show that the system control performance is significantly improved using extremum seeking algorithm compared to traditional methods.