Convergence analysis of hybrid ACO/Nelder-Mead tuning method for PID controller structures with anti-windup

Abstract

Performance of optimization algorithms based on metaheuristics and/or based on derivative-free methods is highly dependent on its parameters. hen, in order to reach a quality solution as fast as possible, the algorithm has to be tuned adequately. A detailed statistical analysis of the system response quality found by Ant Colony Optimization (ACO) based algorithm with respect to discretization of the search space and the number of ants is presented for tuning 4 nonlinear controller structures. he resulting sensitivity curves permit to determine appropriate ACO parameter values to initiate the Nelder-Mead (NM) algorithm. A statistical study of NM convergence is also presented. Using the results of ACO and NM convergence studies has permited to reduce the average ACO-NM computation time by up to 7 times for an equivalent system response quality as compare to the previous