Convergence analysis of an iterative correlation-based controller tuning method

Abstract: A new iterative method using closed-loop data for controller tuning based on the correlation approach is proposed. The main idea is to make the output error between the closed-loop system and a reference model uncorrelated with the reference signal. The controller parameters are calculated as the solution to a correlation equation involving instrumental variables. Convergence and consistency of the controller parameters for two choices of instrumental variables are analyzed. It is shown that the controller parameters converge to their true values independent of the noise characteristics and modeling error. Simulation results confirm the effectiveness of the proposed approach