Nonlinear Predictive Control Based on Inverse System Method

Abstract

To deal with the difficulty of nonlinear inverse model identification of directive inverse control and improve the ability of robustness and anti-interference of the open system, the paper studied the realization of inverse system identification and control using least squares support vector machine (LS-SVM), and proposed a new nonlinear predictive control algorithm based on inverse system method. The method cascades the αth-order inverse model approximated by LS-SVM with the original system to get the composite pseudo-linear system. Then the predictive control method is introduced to the pseudo-linear system. The simulation results show that the combined method does not depend on the accurate mathematical model and has the characteristics of better robustness stability, simpler design process and high tracking accuracy. And this approach is one of the applicable methods for the control of nonlinear systems.