Robust Fault-Tolerant Control for a Class of Second-Order Nonlinear Systems Using an Adaptive Third-Order Sliding Mode Control

Van, Mien; Ge, Shuzhi Sam; Ren, Hongliang

doi:10.1109/tsmc.2016.2557220

Cited by 97 publications

(81 citation statements)

References 53 publications

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“…However, this approach reduces the robustness of the SMC. Another method to reduce the chattering is to employ high‐order SMC (HOSMC) techniques …”

Section: Introductionmentioning

confidence: 99%

Adaptive neural integral sliding‐mode control for tracking control of fully actuated uncertain surface vessels

Van

2019

Intl J Robust & Nonlinear

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This paper develops a novel adaptive neural integral sliding-mode control to enhance the tracking performance of fully actuated uncertain surface vessels. The proposed method is built based on an integrating between the benefits of the approximation capability of neural network (NN) and the high robustness and precision of the integral sliding-mode control (ISMC). In this paper, the design of NN, which is used to approximate the unknown dynamics, is simplified such that just only one simple adaptive rule is needed. The ISMC, which can eliminate the reaching phase and offer higher tracking performance compared to the conventional sliding-mode control, is designed such that the system robust against the approximation error and stabilize the whole system. The design procedure of the proposed controller is constructed according to the backstepping control technique so that the stability of the closed-loop system is guaranteed based on Lyapunov criteria. The proposed method is then tested on a simulated vessel system using computer simulation and compared with other state-of-the-art methods. The comparison results demonstrate the superior performance of the proposed approach. KEYWORDSadaptive control, backstepping control technique, integral sliding-mode control, neural network, surface vessels Int J Robust Nonlinear Control. 2019;29:1537-1557. wileyonlinelibrary.com/journal/rnc

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“…However, this approach reduces the robustness of the SMC. Another method to reduce the chattering is to employ high‐order SMC (HOSMC) techniques …”

Section: Introductionmentioning

confidence: 99%

Adaptive neural integral sliding‐mode control for tracking control of fully actuated uncertain surface vessels

Van

2019

Intl J Robust & Nonlinear

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“…The sliding-mode control has been used extensively to deal with fault-tolerant control (see, e.g. [21]- [22], [25]- [27]). However, the uncertainty existing in the input distribution matrix are rarely considered in the existing work, and specifically, the associate result for high-speed train has not been available.…”

Section: Remarkmentioning

confidence: 99%

“…There are many results about the fault-tolerant sliding-mode control design (see for example [21]- [22], [25]- [27]). However, the considered faults are always assumed to have known bounds or more information of faults, except the contributions mentioned in Remark 4.…”

Section: Remarkmentioning

confidence: 99%

Adaptive Fault-Tolerant Sliding-Mode Control for High-Speed Trains With Actuator Faults and Uncertainties

Mao

Yan

Zhang

et al. 2020

IEEE Trans. Intell. Transport. Syst.

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In this paper, a novel adaptive fault-tolerant slidingmode control scheme is proposed for high-speed trains, where the longitudinal dynamical model is focused, and the disturbances and actuator faults are considered. Considering the disturbances in traction force generated by the traction system, a dynamic model with actuator uncertainties modelled as input distribution matrix uncertainty is established. Then, a new sliding-mode controller with design conditions is proposed for the healthy train system, which can drive the tracking error dynamical system to a pre-designed sliding surface in finite time and maintain the sliding motion on it thereafter. In order to deal with the actuator uncertainties and unknown faults simultaneously, the adaptive technique is combined with the fault-tolerant slidingmode control design together to guarantee that the asymptotical convergence of the tracking errors is achieved. Furthermore, the proposed adaptive fault-tolerant sliding-mode control scheme is extended to the cases of the actuator uncertainties with unknown bounds and the unparameterized actuator faults. Finally, case studies on a real train dynamic model are presented to explain the developed fault-tolerant control scheme. Simulation results show the effectiveness and feasibility of the proposed method.Index Terms-Actuator faults, fault-tolerant sliding-mode control, adaptive control, actuator uncertainty, high-speed train.

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“…Select the best global position best in the swarm and filter signal with corresponding MMA. For example, if the best global position best = [0, 1,3,4,9,2,7,8], the optimal length of SE 1 is 0.0134 and 2 is 0.9278 .…”

Section: Selecting the Lengths Of Se Using Psomentioning

confidence: 99%

“…Condition monitoring-diagnostic methods have an important role in increasing reliability and safety of mechanical systems [1][2][3][4][5][6][7][8]. Rolling element bearings are widely used components in rotating machines and their faults are one of the most frequent reasons for machine failures or performance deterioration (smooth and quiet running).…”

Section: Introductionmentioning

confidence: 99%

Rolling Element Bearing Fault Diagnosis Using Integrated Nonlocal Means Denoising with Modified Morphology Filter Operators

Van

Franciosa

Ceglarek

2016

Mathematical Problems in Engineering

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The impulses in vibration signals are used to identify faults in the bearings of rotating machinery. However, vibration signals are usually contaminated by noise that makes the process of extracting impulse characteristic of localized defect very challenging. In order to effectively diagnose bearing with noise masking vibration signal, a new methodology is proposed using integrated (i) nonlocal means-(NLM-) based denoising and (ii) improved morphological filter operators. NLM based denoising is first employed to eliminate or reduce the background noise with minimal signal distortion. This denoised signal is then analysed by a proposed modified morphological analysis (MMA). The MMA analysis introduces a new morphological operator which is based on Modified-Different (DIF) filter to include only fault relevant impulsive characteristics of the vibration signal. To improve further performance of the methodology the length of the structure element (SE) used in MMA is optimized using a particle swarm optimization-(PSO-) based kurtosis criterion. The results of simulated and real vibration signal show that the integrated NLM with MMA method as well as the MMA method alone yields superior performance in extracting impulsive characteristics of vibrations signals, especially for signal with high level of noise or presence of other sources masking the fault.

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Robust Fault-Tolerant Control for a Class of Second-Order Nonlinear Systems Using an Adaptive Third-Order Sliding Mode Control

Cited by 97 publications

References 53 publications

Adaptive neural integral sliding‐mode control for tracking control of fully actuated uncertain surface vessels

Adaptive neural integral sliding‐mode control for tracking control of fully actuated uncertain surface vessels

Adaptive Fault-Tolerant Sliding-Mode Control for High-Speed Trains With Actuator Faults and Uncertainties

Rolling Element Bearing Fault Diagnosis Using Integrated Nonlocal Means Denoising with Modified Morphology Filter Operators

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