Event-based adaptive neural network asymptotic tracking control for a class of nonlinear systems

Feng, Zhiguang; Li, Rui-Bing; Zheng, Wei Xing

doi:10.1016/j.ins.2022.08.104

Cited by 11 publications

(2 citation statements)

References 41 publications

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“…This improved method will be further verified in the real underwater environment in future research. In addition, other methods such as the perspective of event triggering 40 will be tried to solve the region tracking problem.…”

Section: Discussionmentioning

confidence: 99%

Error scaling–based adaptive region tracking control for autonomous underwater vehicles

Liu

Zhao

Liu

2023

Proceedings of the Institution of Mechanical Engineers, Part I:

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This article investigates the region tracking control problem for an autonomous underwater vehicle subject to external disturbances, model uncertainty, and large initial deviation. In the existing region tracking control schemes, the control signals have a serious chattering phenomenon when autonomous underwater vehicle’s initial deviation is relatively large and the region tracking performance is only investigated from the position information. This article proposes an improved adaptive region tracking control scheme for autonomous underwater vehicle based on error scaling. Specifically, in the improved control scheme, the initial tracking error is artificially reduced by introducing an improved nonlinear mapping function to avoid the singular phenomenon and reduce the violent chattering phenomenon. In addition, the velocity error boundary is amplified by introducing the piecewise Lyapunov function to avoid the overadjustment of adaptive parameters in the developed controller. Meanwhile, it also reduces the frequent switching of control signals in the traditional control scheme which is caused by the pursuit of high-velocity precision. The region tracking performance is analyzed based on Lyapunov theory. Finally, the improved control scheme is applied to an autonomous underwater vehicle for simulation verification, and the comparison results demonstrate the effectiveness of the improved control scheme.

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Section: Discussionmentioning

confidence: 99%

Error scaling–based adaptive region tracking control for autonomous underwater vehicles

Liu

Zhao

Liu

2023

Proceedings of the Institution of Mechanical Engineers, Part I:

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“…The event-based filtering problem of a class of nonlinear NCSs with the method of T-S fuzzy model is investigated in Pan and Yang, 22 and 1 the proposed ETM provides flexibility in balancing the tracking error and network resource utilization. To address the quantization range of the dynamic quantizer, an improved event-triggered protocol related to the quantizer parameters is proposed in Xu et al 23 An asymptotic tracking control strategy based on adaptive neural network is concerned in Feng et al, 24 and an adaptive control law with a single parameter is introduced to achieve the asymptotic tracking performance based on relative threshold event-triggered control signals. In addition, since adaptive event-triggered mechanism (AETM) relies on the real-time state information about the system, the transmission of effective data packets is more accurate.…”

Section: Introductionmentioning

confidence: 99%

Adaptive event–based finite-time H_∞ filtering for networked systems under hybrid attack

Gao,

Xie,

et al. 2024

Proceedings of the Institution of Mechanical Engineers, Part I:

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The event-based finite-time [Formula: see text] filtering problem for networked systems is concerned. A novel hybrid attack model is introduced considering denial-of-service and deception attacks in the communication channel between sampler and filter with an aperiodic form. In order to increase the effectiveness of data transmission in network communication channel and enable the filtering system against attack, an adaptive event–triggered mechanism is proposed. Sufficient condition for ensuring exponential mean-square finite-time boundedness of the filtering error system with an expected [Formula: see text] disturbance attenuation index is obtained. The design of the filter and the adaptive event–triggered mechanism is derived. A practical example is given to demonstrate the effectiveness of the proposed filtering scheme in an active suspension system.

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Extended state observer-based non-singular practical fixed-time adaptive consensus control of nonlinear multi-agent systems

Yang

Wang

et al. 2023

Nonlinear Dyn

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Event-based adaptive neural network asymptotic tracking control for a class of nonlinear systems

Cited by 11 publications

References 41 publications

Error scaling–based adaptive region tracking control for autonomous underwater vehicles

Error scaling–based adaptive region tracking control for autonomous underwater vehicles

Adaptive event–based finite-time H_∞ filtering for networked systems under hybrid attack

Extended state observer-based non-singular practical fixed-time adaptive consensus control of nonlinear multi-agent systems

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Event-based adaptive neural network asymptotic tracking control for a class of nonlinear systems

Cited by 11 publications

References 41 publications

Error scaling–based adaptive region tracking control for autonomous underwater vehicles

Error scaling–based adaptive region tracking control for autonomous underwater vehicles

Adaptive event–based finite-time H∞ filtering for networked systems under hybrid attack

Extended state observer-based non-singular practical fixed-time adaptive consensus control of nonlinear multi-agent systems

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Adaptive event–based finite-time H_∞ filtering for networked systems under hybrid attack