Self-tuning predictive control of nonlinear systems

Abstract

This paper investigates usability of model predictive control (MPC) approach in the area of control of nonlinear systems. A self-tuning predictive controller is introduced and investigated. The controller integrates online identification of an ARX model of a controlled system and a predictive control synthesis on base of the identified model. Various control requirements can be fulfilled by tuning controller's parameters. Both simulation and real-time testing have been performed and are discussed in the paper. The simulation testing was performed in the MATLAB / Simulink environment while the real-time testing has been carried out by the control of nonlinear laboratory models.