Research on grey-model prediction control based on genetic algorithm

This paper presents a grey predictive control method for a class of nonlinear systems with unknown input delay. By using BP neural network, the unknown input delay is identified firstly. The system output is then estimated by the grey predictive algorithm. The output feedback control is fulfilled by PID algorithm which is used to tune its three parameters. By means of combining grey predictive algorithm with genetic algorithm, the method presented in this paper has effective adaptive control performance for the nonlinear systems with the characteristics of unknown input delay and parameter uncertainty. Finally, a numerical example is provided to illustrate the superiority of the proposed method.