Abstract

This paper reports a complete formulation of a model predictive control strategy having guaranteed nominal asymptotic stability. The formulation includes a successive linearisation procedure to obtain a linear model from a non-linear plant model. It gives a complete state-space derivation including long-range prediction, trajectory tracking and modelling of both measured feedforward disturbances and unmeasured stochastic disturbances. Using the dual mode controller concept, the formulation applies a terminal constraint at the end of finite horizon prediction so that outputs reach their steady values asymptotically. The control strategy has been applied in a simulation of a thermal power plant, which is a complex multivariable system based on a non-linear physical model. Although the theoretical results are not entirely new, a complete stable MPC formulation along with its application in a realistic large-scale system is not readily available in MPC literature. A set of simulation results demonstrates the effectiveness of the formulated strategy and compares its performance with finite horizon MPC.