Robustness Of Nonlinear Model Predictive Control

In this thesis, some novel optimization strategies of model predictive control (MFC) are studied from the perspective of methodology. The robust model predictive controloptimization strategies based on the linearization theory and the H∞ control theory areproposed. For a class of nonlinear systems, a H∞-MPC scheme with guaranteedstability is designed. The main work and the novel results of this thesis are as follows:1) The characteristics of receding horizon optimization and the on-line computational issues of model predictive control are analyzed. And the model predictive control theory and the commercial soft are summarized.2) The theory about the choice of the predictive control parameter is proposed. And a worked example is analyzed.3) Some model means about the nonlinear predictive control, especially the linearized model are analyzed.4) In order to improve the robust of the nonlinear predictive control, a recedinghorizon optimization strategy is presented, which is based on the H∞ controland linearization theory. And the stabilization and the algorithm solvability are proved in the theory.