输入饱和线性系统的高性能有界有限时间控制

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Wenyu Ma, Guangyu Liu
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引用次数: 0

摘要

由于执行器的物理限制,现实世界的动态控制系统经常受到输入饱和的影响。这将导致系统的响应性能下降。为此,我们提出了一种基于滑模控制的高性能有界有限时间控制(HP-BFTC)方法,用于具有输入饱和的线性系统的有限时间跟踪。在该方法中,提出了一种新颖的速率调节有限时间稳定性的概念,以获得更好的稳态性能。为了实现速率调节的有限时间稳定性,提出了一种基于滑模控制的有界控制器,其中基于反切函数的有限时间逼近速率可以缓解符号函数引起的抖振,并引入两个控制参数来提高响应性能。在引力估计域内证明了系统的速率调节有限时间稳定性。此外,还提出了一种参数整定原理,以提高闭环系统在瞬态和稳态下的响应性能。通过实例验证了该方法在性能上的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
High Performance Bounded Finite Time Control for Linear Systems With Input Saturation

Real-world dynamical controlled systems are often subject to input saturation due to the physical constraints of actuators. This causes the response performance of the system to be degraded. To this end, we propose a high-performance bounded finite time control (HP-BFTC) method based on sliding mode control for finite time tracking of linear systems with input saturation. In this method, a novel concept of rate regulation finite-time stability is proposed to achieve better steady-state performance. A bounded controller based on sliding mode control is proposed to achieve finite-time stability in rate regulation, wherein a finite time approach rate based on an inverse tangent function is presented to alleviate chattering caused by sign function, and two control parameters are introduced to improve response performance. The rate regulation finite-time stability of the system is proved in the estimated domain of attraction. In addition, a parameter tuning principle is given to enhance the response performance of the closed-loop system in transient and steady state. The superiority of the proposed method in performance is verified by a case study.

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来源期刊
International Journal of Robust and Nonlinear Control
International Journal of Robust and Nonlinear Control 工程技术-工程:电子与电气
CiteScore
6.70
自引率
20.50%
发文量
505
审稿时长
2.7 months
期刊介绍: Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.
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