An Equivalent Aggregation Optimization Strategy in Model Predictive Control
预测控制等效集结优化策略的研究

Aggregation optimization strategies are effective approach to decreasing the on-line computation cost of model predictive controllers. But most of the past aggregation strategies are heuristic, whose control quality cannot keep up with that of the conventional predictive controllers. Starting with the fact that the predictive control algorithm only applies the first moves to a system, this paper presents an equivalent aggregation strategy. We prove that for the unconstralnt and zero terminal constraint MPC, a proper choice of aggregation matrix can make the control quality of the aggregation predictive controller comparable to that of the conventional predictive controller. The algorithm for obtaining the equivalent aggregation matrix is presented, too.