PI-C控制器的时域设计

IF 0.7 4区 计算机科学 Q4 AUTOMATION & CONTROL SYSTEMS At-Automatisierungstechnik Pub Date : 2023-06-01 DOI:10.1515/auto-2022-0142
P. Hippe
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引用次数: 0

摘要

PI-C(比例积分补偿)控制器是一种基于观测器的补偿器,具有包含对象逆模型的积分动作。它们最初是为防止传感器饱和而开发的,在致动器饱和的情况下也很有用。它们允许在环路增益满足圆标准的同时实现近乎完美的干扰衰减。还证明了PI-C控制器可以解决联合输入和输出饱和情况下的饱和问题。到目前为止,PI-C控制器的设计仅在频域中进行了公式化,在MIMO情况下,这需要多项式矩阵的操作。本文介绍了PI-C控制器的状态空间设计。
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Time domain design of PI-C controllers
Abstract PI-C (Proportional-Integral-Compensating) controllers are observer-based compensators with integral action containing an inverse model of the plant. Originally developed for windup prevention in case of sensor saturation they are also useful in the presence of actuator saturation. They allow to achieve a nearly perfect disturbance attenuation while the loop gain satisfies the Circle Criterion. It has also been demonstrated that PI-C controllers can solve the windup problem in case of joint input and output saturation. The design of PI-C controllers has only been formulated in the frequency domain so far which, in the MIMO case, requires the manipulation of polynomial matrices. Here, the state-space design of PI-C controllers is presented.
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来源期刊
At-Automatisierungstechnik
At-Automatisierungstechnik 工程技术-自动化与控制系统
CiteScore
2.00
自引率
10.00%
发文量
99
审稿时长
6-12 weeks
期刊介绍: Automatisierungstechnik (AUTO) publishes articles covering the entire range of automation technology: development and application of methods, the operating principles, characteristics, and applications of tools and the interrelationships between automation technology and societal developments. The journal includes a tutorial series on "Theory for Users," and a forum for the exchange of viewpoints concerning past, present, and future developments. Automatisierungstechnik is the official organ of GMA (The VDI/VDE Society for Measurement and Automatic Control) and NAMUR (The Process-Industry Interest Group for Automation Technology). Topics control engineering digital measurement systems cybernetics robotics process automation / process engineering control design modelling information processing man-machine interfaces networked control systems complexity management machine learning ambient assisted living automated driving bio-analysis technology building automation factory automation / smart factories flexible manufacturing systems functional safety mechatronic systems.
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