An improved design of aggregation-based model predictive control.

Abstract: Linear aggregation in the input is an effective method to reduce the online computational burden of model predictive control (MPC) but at the cost of degradations in the closed-loop performance. In this paper, an improved aggregation-based MPC algorithm is developed to reduce these degradations. In this algorithm, a time-varying base vector is utilized in conjunction with the quasi-equivalent aggregation strategy. Furthermore, by relaxing the constraints with a sequence of reachable sets, a switching strategy is adopted to enlarge the attractive region of the resulting aggregation-based MPC. [Copyright &y& Elsevier]