The Research Of Nonlinear Predictive Control Based On Inverse System Method

The predictive control is researched for the problem of nonlinear system control based on inverse system method. Inverse system method is a feedback linearization method. If the inverse model of nonlinear system exists, the linearization of the nonlinear system is achieved by building inverse model of nonlinear system and cascading the inverse model of nonlinear system with the original system. Then predictive controller is designed in accordance with pseudo-linear system to realize the predictive control for nonlinear system.This paper focuses on the following aspects.First, nonlinear system model is built based on inverse system method. At the premise of the existing of inverse model, the input and output data of nonlinear system are sampling. And then the inverse model of nonlinear system is approximated by BP neural network offline. Simulation results show that there is big error in pseudo-linear system model because of the bad training and generalization ability of BP neural network. Therefore, the Least squares support vector machines modeling is researched in this paper. It overcomes the shortcomings of neural network effectively. Simulation results show that the least squares support vector machines has higher accuracy and better generalization ability than neural network in inverse system modeling.Second, the controller of single variable nonlinear system is designed based on inverse system method. The PID controller, dynamic matrix controller and generalized predictive controller are designed for the reasons that pseudo-linear system does not have robustness for the external disturbances and internal parameter changes. Theoretical analysis and simulation show that PID controller can control the pseudo-linear system with disturbances. But, PID controller can not control large delay system and the optimal parameters are difficult to find. Therefore, dynamic matrix controller and generalized predictive controller are designed for pseudo-linear system in this paper. Further analysis and simulation studies prove that both of the dynamic and static performance of the pseudo-linear system is excellent when disturbances and parameter changes appear. It is also shown that the pseudo-linear system has strong robustness.Third, the control system is designed for multivariable nonlinear system based on inverse system method. The multivariable nonlinear system is discussed based on single variable nonlinear control system. After the multivariable pseudo-linear system is built, the multivariable nonlinear coupling system is stripped into a number of single variable linear systems and dynamic matrix controller group is designed. Simulation results show that the decoupling and linearization function of multivariable inverse system method are limited. And through the designing of dynamic matrix controller group, the pseudo-linear system errors can be made up and the control system can obtain better control performance.Through the theoretical study and simulation analysis in this paper, the predictive controller design method of nonlinear system based on inverse system method can introduce the linear predictive control strategy to nonlinear system and obtain excellent control performance. The paper validates the effectiveness of this method and proposes a novel method for nonlinear predictive control.