自动化学报2017，Vol.43Issue(6)：969-992,24.DOI:10.16383/j.aas.2017.c170082
不确定系统的鲁棒与随机模型预测控制算法比较研究
A Comparative Study on Algorithms of Robust and Stochastic MPC for Uncertain Systems
摘要
Abstract
In recent years,the development of model predictive control (MPC) of uncertain systems has been remarkable.This paper briefly reviews the development of robust MPC and stochastic MPC,summarizes their applications,and expounds and discusses the main algorithms of linear uncertain systems in these two fields.By summarizing their general models,the ways they work,computational complexities,and the ideas they use to ensure recursive feasibility and stability,we reveal the relationship of feasible sets among some of them and unravel the main features of these algorithms and their application situations.Finally,we demonstrate the performance of all the algorithms through certain simulation cases and give some indication on the future development of these two fields.关键词
不确定系统/鲁棒模型预测控制/随机模型预测控制/稳定性/可行性Key words
Uncertain system/robust MPC/stochastic MPC/stability/feasibility引用本文复制引用
谢澜涛,谢磊,苏宏业..不确定系统的鲁棒与随机模型预测控制算法比较研究[J].自动化学报,2017,43(6):969-992,24.基金项目
企业资源计划(ERP)/制造执行系统(MES)与控制系统之间软件互联互通接口规范标准研究和试验验证平台建设,国家自然科学基金(61621002),浙江省自然科学基金杰出青年项目(LR17F030002)资助 Supported by Research on Interface Specification Standard and Test Platform Construction between Control Systems and Enterprise Resource Planning /Manufacturing Execution System,National Natural Science Foundation of China (61621002),Outstanding Young Project of Zhejiang Natural Science Foundation of China (LR17F030002)310027 （ERP）
