A Novel Nonlinear Model Predictive Control Method Based on LMI and Feedback Linearization

Nonlinear model predictive control (NMPC) mainly deals with complex dynamic systems with different kinds of nonlinearities, which is much more difficult to solve than normal linear model predictive. The non-convex optimization method inside MPC is its main challenging problem. A LMI based NMPC method is proposed combined with nonlinear feedback linearization can efficiently convert complex non-convex optimization problem to convex. The method minimizes the upper bound of cost function instead of itself, which can stabilize the whole system and achieve the control performance. A high angle of attack (HAOA) aircraft controller design example is illustrated in the end to demonstrate the validity of proposed method.