Predictive control for nonlinear systems based on Data-drive

To solve the control problem of complex nonlinear system, a control strategy based on Data-drive is proposed. The method builds the local model on-line based on lazy learning algorithm, obtains the optimal control by solving the quadratic optimization problem formulated in a novel generalized predictive control framework, as a result, its adapting and anti-jamming are powerful. Further more, by using hierarchical searching strategy and simplify the solving of control, the searching efficiency is improved and the computation complexity is decreased, so it can realize the real-time control. Simulation results show that the proposed method is effective.