Aggregation based closed-loop MPC with guaranteed performance

Control performance is an important issue for model predictive control (MPC). For the aggregation based MPC controller, where the aggregation strategy is adopted to the control input sequence of MPC, the online computational burden is generally reduced at the cost of control performance. How to guarantee the control performance with the reduced online computational burden is a critical issue for applying the aggregation based MPC. In this paper, the equivalent aggregation strategy is introduced to provide guaranteed performance to the aggregation based closed-loop MPC. For the cases with no constraint and zero terminal constraint, the algorithms to design the equivalent aggregation strategy are developed respectively. Based on them, meanwhile, for the cases with terminal set constraint and state/input constraints, the algorithms to design quasi-equivalent aggregation strategy are presented too. The numerical example verifies the effectiveness of the proposed design.