This article studies the issue of adaptive event-triggered output-feedback control for switched p -normal nonlinear systems with the unknown homogeneous growth rate. A homogeneous output-feedback controller is first designed for nominal nonlinear systems based on adding one power integrator technique. Then, a dynamic gain technique is introduced to deal with the difficulty caused by the unknown homogeneous growth rate. With an elaborate design of the adaptive law of the dynamic gain, a novel adaptive event-triggered output-feedback controller is developed to ensure that the closed-loop system is globally asymptotically stable. Meanwhile, a new analysis way is proposed to prove that the Zeno behavior is excluded in the event-triggered control system. Finally, two examples are provided to indicate the effectiveness of the proposed control method.
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http://dx.doi.org/10.1109/TCYB.2020.3035404 | DOI Listing |
ISA Trans
January 2025
School of Mathematics and Physics, Qingdao University of Science and Technology, Qingdao 266061, China; Qingdao Innovation Center of Artificial Intelligence Ocean Technology, Qingdao 266061, China; The Research Institute for Mathematics and Interdisciplinary Sciences, Qingdao University of Science and Technology, Qingdao 266061, China. Electronic address:
This paper considers the event-triggered adaptive fault-tolerant control (FTC) problem for a class of stochastic nonlinear systems suffering from finite number of actuator failures and abrupt system external failure. Unlike existing event-triggered mechanisms (ETMs), this paper proposes an improved switching threshold mechanism (STM) that effectively addresses the potential system security hazards caused by large signal impulses when both the magnitude size of the controller and its rate of change are too large, while also saving energy consumption. Especially, when the occurrence of both actuator failure and system external failure may lead to over-change rate of the controller, by using the multi-dimensional Taylor network (MTN) approximation technique, the adaptive fault-tolerant control scheme designed based on the improved STM not only has lower resource consumption, but also indirectly improves the control performance of the system by ensuring the system security operation.
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December 2024
School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China. Electronic address:
Denial-of-service (DoS) attacks and antagonistic interactions may exist in complex networks, which will destroy cooperative communication between agents and thus cannot realize collaborative tasks. Therefore, this paper studies time-varying formation tracking (TVFT) of heterogeneous multi-agent systems (HMASs) with DoS attacks and cooperative-antagonistic interactions. It aims to ensure system communication connectivity and allow followers to achieve distributed secure bipartite TVFT.
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January 2025
The School of Electrical and Mechanical Engineering, University of Adelaide, Adelaide, SA, 5005, Australia. Electronic address:
This paper focuses on the design of event-triggered observer-based heterogeneous memory controllers for leader-following multi-agent systems with time-varying topology. In order to save limited on-board resources, a novel adaptive event-triggered strategy based on the nonlinear transformation law of the estimation error is proposed in this paper, which can effectively reduce some unnecessary data transmission due to small fluctuations after the estimation error converges. Then, a more general topology structure described by an interval type-2 fuzzy model is adopted, which contains both nonlinear time-varying law and uncertain parameters.
View Article and Find Full Text PDFNeural Netw
March 2025
School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210023, China. Electronic address:
This article investigates the problem of adaptive fixed-time optimal consensus tracking control for nonlinear multiagent systems (MASs) affected by actuator faults and input saturation. To achieve optimal control, reinforcement learning (RL) algorithm which is implemented based on neural network (NN) is employed. Under the actor-critic structure, an innovative simple positive definite function is constructed to obtain the upper bound of the estimation error of the actor-critic NN updating law, which is crucial for analyzing fixed-time stabilization.
View Article and Find Full Text PDFThe leader-following consensus issue for general linear multiagent systems (MASs) is investigated under event-triggered communication (ETC). Based on the output measurement of agent, two novel adaptive dynamic event-triggered (ADET) strategies for synchronous and asynchronous ETC are proposed, in which adaptive triggering parameters and time-varying threshold are introduced. Simultaneously, the corresponding control protocols are developed under the ADET strategies.
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