This paper presents an adaptive fault-tolerant control (FTC) scheme for a class of nonlinear uncertain multi-agent systems. A local FTC scheme is designed for each agent using local measurements and suitable information exchanged between neighboring agents. Each local FTC scheme consists of a fault diagnosis module and a reconfigurable controller module comprised of a baseline controller and two adaptive fault-tolerant controllers activated after fault detection and after fault isolation, respectively. Under certain assumptions, the closedloop system's stability and leader-follower consensus properties are rigorously established under different modes of behavior of the FTC system, including the time-period before possible fault detection, between fault detection and possible isolation, and after fault isolation.
This paper presents an adaptive fault-tolerant control (FTC) scheme for a class of nonlinear uncertain multi-agent systems. A local FTC scheme is designed for each agent using local measurements and suitable information exchanged between neighboring agents. Each local FTC scheme consists of a fault diagnosis module and a reconfigurable controller module comprised of a baseline controller and two adaptive fault-tolerant controllers activated after fault detection and after fault isolation, respectively. Under certain assumptions, the closedloop system's stability and leader-follower consensus properties are rigorously established under different modes of behavior of the FTC system, including the time-period before possible fault detection, between fault detection and possible isolation, and after fault isolation.
This paper focuses on developing a distributed leader-following fault-tolerant tracking control scheme for a class of high-order nonlinear uncertain multi-agent systems. Neural network based adaptive learning algorithms are developed to learn unknown fault functions, guaranteeing the system stability and cooperative tracking even in the presence of multiple simultaneous process and actuator faults in the distributed agents. The time-varying leader's command is only communicated to a small portion of follower agents through directed links, and each follower agent exchanges local measurement information only with its neighbors through a bidirectional but asymmetric topology. Adaptive fault-tolerant algorithms are developed for two cases, i.e., with full-state measurement and with only limited output measurement, respectively. Under certain assumptions, the closed-loop stability and asymptotic leader-follower tracking properties are rigorously established.
This paper presents a distributed integrated fault diagnosis and accommodation scheme for leader-following formation control of a class of nonlinear uncertain second-order multi-agent systems. The fault model under consideration includes both process and actuator faults, which may evolve abruptly or incipiently. The time-varying leader communicates with a small subset of follower agents, and each follower agent communicates to its directly connected neighbors through a bidirectional network with possibly asymmetric weights. A local fault diagnosis and accommodation component are designed for each agent in the distributed system, which consists of a fault detection and isolation module and a reconfigurable controller module comprised of a baseline controller and two adaptive fault-tolerant controllers, activated after fault detection and after fault isolation, respectively. By using appropriately the designed Lyapunov functions, the closed-loop stability and asymptotic convergence properties of the leader-follower formation are rigorously established under different modes of the fault-tolerant control system. KEYWORDS adaptive control, fault-tolerant control, formation control, multi-agent systems, nonlinear uncertain systems Int J Robust Nonlinear Control. 2018;28:4287-4308.wileyonlinelibrary.com/journal/rnc
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