An Interval Predictor-Based Robust Control for a Class of Constrained Nonlinear Systems

This paper proposes the design of a robust sampled-time controller to stabilize continuous-time nonlinear systems, taking into account state and input constraints. The proposed controller comprises the design of a robust control law, which is based on an interval predictor-based state-feedback controller and a Model Predictive Control (MPC) approach, which deals with the state and input constraints. The interval predictor-based state-feedback controller is designed based on a Lyapunov function approach that provides a safe set, where the state constraints are not transgressed. Out this set, the MPC is activated guaranteeing the fulfillment of the state and input constraints. The proposed switched control strategy guarantees the practical Uniform Asymptotic Stability of the considered nonlinear systems. A constructive method, based on linear matrix inequalities (LMIs), is proposed to compute the controller gains and the state of the system is not required. Some simulation results illustrate the feasibility of the proposed scheme.