Data-driven-based sliding-mode dynamic event-triggered control of unknown nonlinear systems via reinforcement learning

Wang, Tengda; Zong, Guangdeng; Zhao, Xudong; Xu, Ning

doi:10.1016/j.neucom.2024.128176

Neurocomputing

2024

DOI: 10.1016/j.neucom.2024.128176

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Data-driven-based sliding-mode dynamic event-triggered control of unknown nonlinear systems via reinforcement learning

Tengda Wang,

Guangdeng Zong,

Xudong Zhao

et al.

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Cited by 36 publications

References 56 publications

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

Liu,

Zhao,

Zhang

et al. 2024

Asian Journal of Control

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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.

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

Liu,

Zhao,

Zhang

et al. 2024

Asian Journal of Control

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A Unified Adaptive Event‐Triggered Output Feedback Consensus for Multi‐Agent Systems With or Without Output Constraints

Huang,

Karimi,

Niu

et al. 2024

Intl J Robust & Nonlinear

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This paper is dealing with the problem of adaptive event‐triggered leader‐follower consensus for multi‐agents systems with output constraints and dead‐zone inputs. By introducing an advanced nonlinear mapping technique to obtain the unconstrained auxiliary variables of constrained system states, a new systems model without output constraints is constructed. Unlike existing schemes, the proposed strategy can be used in both constrained and unconstrained situations without requiring changes to the control structure. Moreover, a state estimator is constructed to observe the unavailable states. To conserve communication resources, an event‐triggered rule with a dynamic threshold is designed to decrease superfluous information transmissions from the controller to the actuator. It is proven that all signals in closed‐loop systems are ultimately bounded, and the system output does not violate the given constraint range. At last, a numerical simulation example is provided to confirm the correctness and efficiency of the proposed method.

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Towards improving context-aware applications using link quality induction and self-calibrated ultra-wide band localization systems

Lai,

Zhou,

et al. 2024

Computing

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Data-driven-based sliding-mode dynamic event-triggered control of unknown nonlinear systems via reinforcement learning

Cited by 36 publications

References 56 publications

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

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

A Unified Adaptive Event‐Triggered Output Feedback Consensus for Multi‐Agent Systems With or Without Output Constraints

Towards improving context-aware applications using link quality induction and self-calibrated ultra-wide band localization systems

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