Adaptive neural hierarchical sliding mode control for uncertain switched underactuated nonlinear systems against unmodeled dynamics and input delay

IF 2.7 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Shanlin Liu, Ning Zhao, Liang Zhang, Ning Xu
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引用次数: 0

Abstract

In this article, the issue of adaptive control for switched underactuated systems subject to input delay and unmodeled dynamics is investigated. Unlike traditional backstepping methods, this paper introduces a hierarchical sliding mode control (HSMC) approach that can improve the response rate and robustness of the controlled plant. Under the framework of this control method, a top hierarchical sliding mode surface (HSMS) containing all the information of state variables and an effective controller consisting of switching control laws and equivalent control laws are constructed. In the control design process, an auxiliary system and a hyperbolic tangent function are introduced to compensate for the impact of input delay while avoiding singularity problems. In addition, a dynamic signal is designed to compensate the effect of the unmodeled dynamics. The designed controller can ensure that all signals of the closed-loop system, including states of the auxiliary system, are bounded. Finally, the benefits of the proposed HSMC approach are confirmed by two simulation examples.

不确定切换欠驱动非线性系统抗未建模动力学和输入延迟的自适应神经递阶滑模控制
本文研究了受输入延迟和未建模动力学影响的切换欠驱动系统的自适应控制问题。与传统的反步控制方法不同,本文引入了一种层次滑模控制方法,可以提高被控对象的响应率和鲁棒性。在该控制方法的框架下,构造了包含状态变量全部信息的顶层分层滑模曲面(HSMS)和由切换控制律和等效控制律组成的有效控制器。在控制设计过程中,引入辅助系统和双曲正切函数来补偿输入延迟的影响,同时避免了奇异性问题。此外,还设计了一个动态信号来补偿未建模动力学的影响。所设计的控制器能够保证闭环系统的所有信号,包括辅助系统的状态都是有界的。最后,通过两个仿真实例验证了该方法的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Asian Journal of Control
Asian Journal of Control 工程技术-自动化与控制系统
CiteScore
4.80
自引率
25.00%
发文量
253
审稿时长
7.2 months
期刊介绍: The Asian Journal of Control, an Asian Control Association (ACA) and Chinese Automatic Control Society (CACS) affiliated journal, is the first international journal originating from the Asia Pacific region. The Asian Journal of Control publishes papers on original theoretical and practical research and developments in the areas of control, involving all facets of control theory and its application. Published six times a year, the Journal aims to be a key platform for control communities throughout the world. The Journal provides a forum where control researchers and practitioners can exchange knowledge and experiences on the latest advances in the control areas, and plays an educational role for students and experienced researchers in other disciplines interested in this continually growing field. The scope of the journal is extensive. Topics include: The theory and design of control systems and components, encompassing: Robust and distributed control using geometric, optimal, stochastic and nonlinear methods Game theory and state estimation Adaptive control, including neural networks, learning, parameter estimation and system fault detection Artificial intelligence, fuzzy and expert systems Hierarchical and man-machine systems All parts of systems engineering which consider the reliability of components and systems Emerging application areas, such as: Robotics Mechatronics Computers for computer-aided design, manufacturing, and control of various industrial processes Space vehicles and aircraft, ships, and traffic Biomedical systems National economies Power systems Agriculture Natural resources.
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