The Research Of Nonlinear Robust Predictive Control System

Nonlinear model predictive control (NMPC) is an important branch of control theory. After about twenty years of development, the research of NMPC has reached a relative mature stage. But as NMPC is very complex, some fundamental problems, such as stability and robustness, have not been well resolved, blocking the development of NMPC and its industrial application. Therefore, current research of NMPC still focus on the problems mentioned above. This paper mainly introduces general ideas of designing NMPC based on linear matrix inequalities (LMI), and respectively designs NMPC for polynomial model and norm-bounded differential inclusion model. For the situation that actual system state is not fully known, an output feedback robust constrained model predictive control based on state observer is designed in the paper. At last, simulation research is carried out according to each situation above, and the results show the methods are effective.