Event-triggered sliding mode control with adaptive neural networks for uncertain nonlinear systems

Wang, Nana; Hao, Fei

doi:10.1016/j.neucom.2021.01.055

Cited by 32 publications

(14 citation statements)

References 40 publications

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“…Thus, how to design an adaptive control scheme to deal with the unknown bound of uncertainties while ensuring the performance on resource utilization is still a challenge. Wang and Hao 19 studied second‐order uncertain nonlinear systems employing nonsingular fast terminal sliding mode control and adaptive neural network strategy. But these results could not be directly extended to multi‐put nonlinear systems with coupling items, which is the motivation of this work.…”

Section: Introductionmentioning

confidence: 99%

“…Different from Reference 14, the uncertainties are not prior information to the systems. Unlike Reference 19 which studied second‐order nonlinear systems by adaptive neural network, this article considers the stability problem of multi‐input uncertain Euler–Lagrange systems. (2) It is proved that Zeno behavior could be avoided and there exists a positive low bound of the inter‐event times.…”

Section: Introductionmentioning

confidence: 99%

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Event‐based adaptive sliding mode control for Euler–Lagrange systems with parameter uncertainties and external disturbances

Wang

Hao

2022

Intl J Robust & Nonlinear

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This article studies the robust tracking control problem for a class of uncertain Euler-Lagrange systems. An adaptive sliding mode control strategy is proposed to address the robust stability of the closed-loop systems with external disturbances and parameter uncertainties. An adaptive parameter estimator is constructed in the sensor node to deal with the unknown bound of uncertainties, and an event-triggering detector is located between the sensor node and the controller node. The introduction of event-triggering condition is introduced, reducing the utilization on communication resources and the number of control execution. In this event-triggered strategy, the closed-loop systems reach the practical sliding mode band and the band could be adjusted. Moreover, the event-triggering condition can make sure that Zeno behavior does not occur. Finally, simulation results on 2-link robotic manipulator are provided to illustrate the effectiveness and feasibility of the proposed control scheme.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Event‐based adaptive sliding mode control for Euler–Lagrange systems with parameter uncertainties and external disturbances

Wang

Hao

2022

Intl J Robust & Nonlinear

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“…The observer-based SMC problem of phasetype semi-Markovian jump systems was discussed in [4]. In [8], the authors investigated the issue of SMC with adaptive neural networks for a class of nonlinear uncertain systems. A novel asynchronous sliding mode control scheme is proposed in [9], which guarantees the desired finite-time boundedness of Markovian jump systems with sensor and actuator faulty signals.…”

Section: Introductionmentioning

confidence: 99%

Finite-Time Sliding Mode Control for Uncertain Neutral Systems With Time Delays

Zhang¹,

Wang

2021

IEEE Access

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The finite-time stability (FTS) problem of uncertain neutral time-delay systems via a sliding mode control (SMC) approach is discussed in this paper. First, we construct a suitable sliding mode surface and an SMC law, which can guarantee the system states can reach the sliding mode surface in a finite time and maintain the sliding mode. Then, through the Lyapunov stability theory and the inequality techniques, the finite time stability of the closed-loop system during reaching phase and sliding mode phase is studied, a set of sufficient conditions which ensure the system to be finite-time stability is developed. Finally, a numerical simulation example is given to illustrate the effectiveness of the results.INDEX TERMS Finite-time stability, sliding mode control, uncertain, neutral time-delay systems.

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“…However, if the bounds are unknown, it will be a difficult problem. For the requirement of the upper limit value of unknown components, many control schemes have been proposed based on a combination of Neural Networks (NNs), 25 Fuzzy Logic Systems (FLSs), 26 or Adaptive Control Laws (ALCs) 27 with SMC. Although the behavior of unknown components can be well learned by these approaches.…”

Section: Introductionmentioning

confidence: 99%

Design of a non-singular fast terminal sliding mode control for second-order nonlinear systems with compound disturbance

Kolahi

Gharib

Heydari

2021

Proceedings of the Institution of Mechanical Engineers, Part C:

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This paper investigates a new disturbance observer based non-singular fast terminal sliding mode control technique for the path tracking and stabilization of non-linear second-order systems with compound disturbance. The compound disturbance is comprised of both parametric and non-parametric uncertainties. While warranting fast convergence rate and robustness, it also dominates the singularity and complex-value number issues associated with conventional terminal sliding mode control. Furthermore, due to the estimation properties of the observer, knowledge about the bounds of the uncertainties is not required. The simulation results of two case studies, the velocity and path tracking of an autonomous underwater vehicle and the stabilization of a chaotic Φ6-Duffing oscillator, validate the efficacy of the proposed method.

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Event-triggered sliding mode control with adaptive neural networks for uncertain nonlinear systems

Cited by 32 publications

References 40 publications

Event‐based adaptive sliding mode control for Euler–Lagrange systems with parameter uncertainties and external disturbances

Event‐based adaptive sliding mode control for Euler–Lagrange systems with parameter uncertainties and external disturbances

Finite-Time Sliding Mode Control for Uncertain Neutral Systems With Time Delays

Design of a non-singular fast terminal sliding mode control for second-order nonlinear systems with compound disturbance

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