A Controller-Dynamic-Linearization-Based Model Predictive Control Approach for SISO Discrete-time Nonlinear Systems

In this paper, a novel model predictive control based on the dynamic linearization technology is proposed for a class of single-input and single-output nonlinear discrete-time systems. By using the compact form dynamic linearization method, the designed controller is in advance constructed as a parameterized control law, which is an equivalent expression of an ideal controller. Instead of optimizing a sequence of control inputs for the traditional model predictive control, the issue is transformed into the parameter optimization of the constructed control law under the model predictive control scheme in closed loop. The effectiveness of the proposed model predictive control is demonstrated by a numerical example on discrete-time linear and nonlinear system through comparing with the traditional model predictive control.