无偏模型预测控制综述

无偏(静差)模型预测控制(Model predictive control, MPC)的设计目标是使被控变量渐近地跟踪设定值, 这类控制方法直接关系到闭环系统的跟踪性能和抗扰性能.由于可以有效处理不可测扰动、模型失配等, 无偏MPC具有很强的工程应用价值, 但是在理论方面并没有得到充分重视.近30年来, 围绕无偏MPC的原理、分析和设计展开了一系列的研究工作, 并取得了系统性的研究成果.当前的一些研究结果大多分散在不同的参考文献中, 缺少全面的梳理和呈现.本文的主要工作包括回顾常见无偏控制方法, 综述当前无偏MPC的研究进展, 并探讨一些潜在的研究方向.

A Survey on Ofiset-free Model Predictive Control

The goal of offset-free MPC (Model predictive control) is to drive the controlled variables to the desired setpoints asymptotically. Due to the ability to cope with unmeasured disturbances and/or model mismatch, offset-free control strategies are directly related to the tracking performance and disturbance rejection performance. Offset-free MPC is fundamental for practical implementation, however, is often overlooked in academic researches. Great achievements have been made in the area of offset-free MPC over the last three decades. The existing results scatter in many academic papers and books, and there are few systemic discussions. This paper aims to shed some light on the theory and design of offset-free MPC, including common offset-free control strategies, current research activities, and some possible directions in the future.