Model Predictive and Inversive Control for State Transition of Dynamics Systems

Abstract

In this paper, a new method of state stability, transition and tracking control for dynamics system based on model prediction and inversion is introduced. The estimation of system state bias in the future is obtained by model prediction. According to the dynamics evolution law of the controlled object, the control command to eliminate the future deviation is obtained by dynamics inversion. The compensation control is designed for the current and historical state deviations, and a state control method based on dynamics model of the controlled object is constructed. This method can be widely applied to various forms of control, and can better realize the state transition, tracking and stability control of dynamics system under the time constraint. The controller can be self-organized according to the model of the controlled object, and the parameters of the controller can be adjusted adaptively. It has good robustness to load/disturbance and deviations of model parameter, state measurement and control execution. The characteristics of this method are discussed, a simulation of rocket attitude control is given and the future research focus of this method is prospected.