Fully Actuated System Approach for Control: An Overview

IF 9.4 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Cybernetics Pub Date : 2024-09-24 DOI:10.1109/TCYB.2024.3457584
Guang-Ren Duan
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Abstract

Fully actuated system (FAS) approach was proposed in 2020 and 2021 as a general framework for control system analysis and design based on a newly discovered general type of fully actuated models for dynamical systems. Due to its great advantages and power in dealing with complicated nonlinear time-varying and time-delay systems with possibly nonholonomic features, it has attracted much attention in the control community immediately since its birth. By now, numerous results have been produced for analysis and control of various types of complicated systems, which cover the topics of adaptive control, robust control, predictive control and fault-tolerant control, and involve time-varying and time-delay systems, discrete-time systems, stochastic systems and even impulsive systems. Meanwhile, a large number of applications have also been carried out. These include spacecraft control, aircraft and quadrotor control, robot control and control of power electronic systems and servo systems. In this article, an overview of the FAS approach is presented, ranging from models, basic theories, and control techniques to applications.
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全驱动系统控制方法:概述
完全驱动系统(FAS)方法是在2020年和2021年提出的,作为控制系统分析和设计的一般框架,该框架基于新发现的动力系统的一般类型的完全驱动模型。由于它在处理可能具有非完整特征的复杂非线性时变和时滞系统方面的巨大优势和能力,自诞生以来就受到了控制界的广泛关注。到目前为止,对于各种类型的复杂系统的分析和控制已经产生了许多成果,涵盖了自适应控制、鲁棒控制、预测控制和容错控制等主题,涉及时变系统和时滞系统、离散系统、随机系统甚至脉冲系统。同时,也进行了大量的应用。这些包括航天器控制,飞机和四旋翼控制,机器人控制和控制电力电子系统和伺服系统。在这篇文章中,概述了FAS方法,从模型、基本理论、控制技术到应用。
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来源期刊
IEEE Transactions on Cybernetics
IEEE Transactions on Cybernetics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
25.40
自引率
11.00%
发文量
1869
期刊介绍: The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.
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