Optimal design of model following control with uncertain disturbance by using genetic algorithms

Abstract

Optimal design of model following control with uncertain disturbance is to determine some control parameters such that the output of the plant is regulated to follow the output of reference model. In order to obtain the values of optimal control parameters, this paper presents a genetic algorithm for the optimal design of model following control in which there are nonlinear disturbance and uncertain parameters. The effectiveness of the proposed algorithm is also illustrated by some numerical examples.