Fuzzy Adaptive Fault-Tolerant Control for Non-identifiable Multi-agent Systems under Switching Topology
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Fuzzy Adaptive Fault-Tolerant Control for Non-identifiable Multi-agent Systems under Switching Topology Ao Zhang1 • Chao Deng2
Received: 12 April 2020 / Revised: 29 May 2020 / Accepted: 13 July 2020 Taiwan Fuzzy Systems Association 2020
Abstract This paper considers the leader-following consensus problem for linear multi-agent systems (MASs) with actuator faults, matched unknown nonlinearity and nonidentifiable uncertainty under switching network topology for studying. A novel distributed switching fault-tolerant controller is established by approximating the nonlinear dynamics using a fuzzy logic system and by developing adaptive update laws with switching mechanisms. Besides, by introducing an adaptive mechanism to estimate the norm of weight vectors in the FLS, the developed controller can not only reduce the number of adaptive parameters but also is effective to compensate for unknown nonlinearity under the influence of actuator faults. Furthermore, it can be shown that the consensus errors are uniformly ultimately bounded by utilizing the proposed method. Compared with the existing MASs’ results with switching network topology, the nonlinearity considered is completely unknown and fewer adaptive parameters are used to counteract the influence of nonlinearity. Finally, the efficiency and effectiveness of the developed approach are demonstrated by an illustrative example. Keywords Fuzzy logic system Fault-tolerant control Adaptive control Actuator faults
& Chao Deng [email protected] 1
Department of Foundational Courses, Shenyang Institute of Science and Technology, Shenyang 110167, China
2
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore
1 Introduction During the past decade, multi-agent systems (MASs) have attracted increasing attention from both the academia and the industry owing to its broad range of applications, such as coordination of multiple robots, the platoon of unmanned aerial vehicles [1], distributed energy storage [2] and so forth [3–5]. A fundamental challenge to the MASs is how to develop a control algorithm based on the interactions among neighbors such that all the agents can reach a specified common state [6]. Leader-following consensus, which mainly aims to motivate members to follow the leader, is an interesting topic pertaining to the consensus issue [7]. Much effort has been directed at solving the leader-following consensus problem of MASs with various agent dynamics, communication environments, etc. [8]. It is well known that nonlinearity exists in almost all practical systems, which is always elusive for the designer. It has been shown that the fuzzy logic system (FLS) can effectively estimate the unknown nonlinearity [9, 10]. As a result, some valuable FLS-based distributed controllers have been devised to settle the consensus issue of nonlinear MASs [11, 12]. By developing an FLS-based controller, the authors of [11] solve the consensus problem of nonlinear high-order MASs. For more general MASs, which contain the
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