Stochastic Tubes in Model Predictive Control With Probabilistic Constraints

作者：Mark Cannon, B. Kouvaritakis, Saša V. Raković, Qifeng Cheng · 发表于：IEEE Transactions on Automatic Control · 年份：2010 · DOI：10.1109/tac.2010.2086553 · 被引用次数：245 · 研究领域：Advanced Control Systems Optimization、Fault Detection and Control Systems、Control Systems and Identification

Stochastic model predictive control (MPC) strategies can provide guarantees of stability and constraint satisfaction, but their online computation can be formidable. This difficulty is avoided in the current technical note through the use of tubes of fixed cross section and variable scaling. A model describing the evolution of predicted tube scalings facilitates the computation of stochastic tubes; furthermore this procedure can be performed offline. The resulting MPC scheme has a low online computational load even for long prediction horizons, thus allowing for performance improvements. The efficacy of the approach is illustrated by numerical examples.