Indirect Adaptive MPC for Output Tracking of Uncertain Linear Polytopic Systems

We present an indirect adaptive model predictive control algorithm for output tracking of linear systems with polytopic uncertainty. The proposed approach is based on the velocity form of the system model, and achieves input-to-state stable output tracking with respect to the parameter estimation error and the rate of change of time-varying references. For the constrained case, recursive feasibility is achieved by including robust constraints designed from a robust control invariant set for the system model, and terminal constraints designed from a positive invariant set for the velocity model. Simulation results for a numerical example and an air conditioning control application demonstrate the method.