未知时变控制方向和执行器故障下非线性系统的预定性能跟踪控制

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Teng-Fei Fang, Huimin Wang, Guang-Hong Yang
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引用次数: 0

摘要

研究了一类具有未知时变控制方向和执行器故障的不确定严格反馈系统的规定性能控制问题。提出了一种低复杂度的控制方案,其中包含了一种新的控制方向确定方法。与Nussbaum增益和参数估计等主流方法相比,该方法克服了控制器设计中执行器故障导致的控制方向时变未知的挑战。首先,定义了距离函数,并在此基础上建立了控制方向识别机制。结合基于ppc的控制律,设计了一种未知时变控制系数下严格反馈系统的状态反馈容错控制方案。随后,利用矛盾证明的思想,证明了在该方案下,系统跟踪误差可以保持在预定义的性能准则内,同时保证任何闭环信号的有界性。最后,通过两组仿真算例分别验证了所提方案在未知时变控制方向和常规未知控制方向下的有效性和优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prescribed Performance Tracking Control of Nonlinear Systems Under Unknown Time-Varying Control Direction and Actuator Faults

This article investigates the prescribed performance control (PPC) problem for a class of uncertain strict-feedback systems with unknown time-varying control direction and actuator faults. A low-complexity control scheme which contains a novel control direction determination approach is proposed herein. Compared with the mainstream methods such as the Nussbaum gain and parameter estimation, the newly proposed scheme overcomes the challenge of the unknown time-varying control direction caused by actuator faults in the controller design. First, a distance function is defined, upon which a mechanism for identifying the control direction is developed. Combined with the PPC-based control law, a state feedback fault-tolerant control scheme for strict-feedback systems under unknown time-varying control coefficient is designed. Subsequently, utilizing the idea of proof by contradiction, it has been proven that under this scheme, the system tracking error can be maintained within the predefined performance criteria, while ensuring the boundedness of any closed-loop signals. Lastly, the effectiveness and merits of the proposed scheme under unknown time-varying control direction and conventional unknown control direction are verified by two sets of simulation examples, respectively.

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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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