MPC for tracking of constrained nonlinear systems

This paper deals with the tracking problem for constrained non-linear systems using a model predictive control (MPC) law. MPC provides acontrol law suitable for regulating constrained linear and nonlinear systems toa given target steady state. However, when the target operating point changes,the feasibility of the controller may be lost and the controller fails to track thereference. In this paper, a novel MPC for tracking changing constant referencesis presented. This controller extend a recently presented MPC for tracking forconstrained linear systems to the nonlinear case. The main characteristics of thiscontroller are: considering an artificial steady state as a decision variable, minimizing a cost that penalizes the error with the artificial steady state, addingto the cost function an additional term that penalizes the deviation betweenthe artificial steady state and the target steady state (the so-calledoffset costfunction) and considering an invariant set for tracking as extended terminalconstraint. The properties of this controller has been tested on a constrainedCSTR simulation model.