执行器饱和受限不确定系统的次序优化多步预测控制  

Multi-step predictive control for input-saturated uncertain systems based on sequential optimization scheme

作　　者：张浪文[1] 谢巍[2] ZHANG Lang-wen XIE Wei(College of Automation Science and Technology, South China University of Technology, Guangzhou 510640, China Key Laboratory of Autonomous Systems and Networked Control of Ministry of Education, South China University of Technology, Guangzhou 510640, China)

机构地区：[1]华南理工大学自动化科学与工程学院,广州510640 [2]华南理工大学自主系统与网络控制教育部重点实验室,广州510640

出　　处：《控制与决策》2017年第8期1499-1504,共6页Control and Decision

基　　金：中国博士后科学基金项目(2016M592488);中央高校基本科研业务费专项资金项目(2017BQ098);工业控制技术国家重点实验室开放课题(ICT170340);广东省科技计划项目(2016B090927007);广东省引进创新创业团队计划项目(2016YT03G125);广州市科技项目(201707010152)

摘　　要：设计一种次序优化机制,提出一类饱和受限不确定系统的次序优化多步预测控制方法.将系统的输入分解成多个子集合,在各采样周期仅对其中一个集合的输入进行优化,待优化的输入保持上一优化值.针对每个输入集合,确定闭环系统的不变集条件,将次序优化预测控制器设计问题转化成"最小-最大"优化问题,通过求解一组线性矩阵不等式问题得到控制器.仿真算例表明,采用次序优化预测控制方法可以减少控制器的设计时间.This paper presents a multi-step predictive control algorithm for input saturated systems by designing a sequential optimization scheme. The control inputs are divided into several subsets, and only one subset of inputs are optimized at each time instant. The inputs that are not optimized at the current instant remains the latest optimized one. For each input set, a set invariance condition is identified, and the multi-step predictive controller design problem is transformed into a ＂min-max＂ optimization problem. The multi-step predictive controller is obtained by solving linear matrix inequalities（LMIs）. The simulation results show that the proposed multi-step predictive control algorithm has the advantage in reducing the computation time in controller design.

关 键 词：饱和受限 不确定系统 次序优化 预测控制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]