摘要：AbstractIn this article, a Model Predictive Control (MPC) scheme that, by taking advantage of the control problem time invariant ingredients, replaces as much as possible the on-line computational burden of the conventional schemes, by off-line computation, is presented and its asymptotic stability shown. The generated data is stored onboard in look-up tables and recruited and adapted on-line with small computation effort according to the real-time context specified by communicated or sensed data. This scheme is particularly important to the increasing range of applications exhibiting severe real-time constraints. The approach presented here provides a better re-conciliation of onboard resources optimization with state feedback control - to deal with the typical a priori high uncertainty - while managing the formation with a low computational budget which otherwise might have a significant impact in power consumption.
