Neuro-Adaptive Fault-Tolerant Approach for Active Suspension Control of High-Speed Trains

Li, Danyong; Song, Yongduan; Cai, Wenchuan

doi:10.1109/tits.2015.2409296

Cited by 30 publications

(8 citation statements)

References 30 publications

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“…The objective now is to design a sliding-mode controller such that the error system (10)-(11) can be driven to the sliding surface (13) in finite time and maintains the sliding motion thereafter. 4 Sliding-mode controller design. For train dynamic system (3)-(4), consider the controller…”

Section: Casementioning

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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Section: Casementioning

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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“…HSTs consist of a vehicle body with secondary suspension element, bogie with primary suspension elements and wheels. The mathematical equations of the dynamics of the lateral and roll motion of the HST are given as 12 1) Body lateral dynamics…”

Section: Mechanical Modelling Of An Hstmentioning

confidence: 99%

“…An adaptive fuzzy-based fault tolerant control of multiple HSTs is reported in Guo et al 11 based on the PI-SMC approach. Similarly, neural network (NN)-based fault tolerant control 12 is applied on the HST to control the lateral and roll motion subjected to parametric uncertainty. A delay-dependent velocity tracking controller based on H 1 control approach is designed for the multiparticle model of an HST.…”

Section: Introductionmentioning

confidence: 99%

“…Dynamical model of the HST. 12 to deal with unknown time-varying input gains and bounded modelling errors in Chen et al 28 An adaptive asymptotic control design for a multivariable system based on one-parameter estimation approach has been investigated. 29 Motivated by the above observations, an adaptive neuro-observer (ANO)-based dynamic surface controller (DSC) design for the nonlinear model of an HST system has been considered in this paper.…”

Section: Introductionmentioning

confidence: 99%

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Design of an adaptive neuro-observer-based feedback controller for high-speed trains with parametric uncertainties

Patel

Pratap

2018

Proceedings of the Institution of Mechanical Engineers, Part F:

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An adaptive observer-based controller design for the nonlinear model of a high-speed train is demonstrated in this paper. A high-speed train belongs to the class of multivariable and coupled dynamic system with a higher degree of nonlinearities and uncertainties. The radial basis function neural network is used for the approximation of these nonlinearities and uncertainties. Using this approximation, an adaptive neuro-observer is designed for the estimation of the unavailable states of the high-speed train for measurement. Using one-to-one nonlinear mapping, the high-speed train plant and the adaptive neuro-observer are remodelled in a pure feedback form without any constraints on states. On the basis of the adaptive neuro-observer, an adaptive dynamic surface controller is designed for the high-speed train system. The upper bounds of the actual controller gains of the high-speed train need not be known whereas the lower and upper bounds of the virtual controller gain require prior knowledge. The tuning of the design parameters has been done online in the proposed observer/controller. The closed-loop stability and convergence have been analysed through a formal proof based on the Lyapunov approach. The enhanced performance of the high-speed train with the proposed controller is compared with the backstepping control approach and demonstrated using simulation studies.

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“…ride comfort, handling stability, and road holding capability) of the vehicle suspension system are usually in conflict with each other. Therefore, many control approaches have been implemented on active suspension systems to maintain a balance among these conflicting requirements, such as neural network control, 7 sliding model control, 8 backstepping control, 9 adaptive control, 10 preview control, 11 and robust H ∞ control. Among the above approaches, the robust H ∞ control method has been confirmed as a valid approach to manage the trade-off among the three conflicting performances and achieve an overall optimization of requirements.…”

Section: Introductionmentioning

confidence: 99%

Event-triggered fuzzy control for vehicle nonlinear suspension systems with time delay

Jia

Zhang

Zheng

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part I:

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This article investigates the adaptive event-triggered fuzzy control problem for vehicle suspension systems with nonlinear characteristics and time delay. First, to describe the vehicle suspension system with nonlinear components, a Takagi-Sugeno fuzzy suspension model is established via local linear regression method. Second, considering that the communication bandwidth is limited, an adaptive event-triggered strategy is employed to acquire a higher efficiency in terms of saving the transmission resource. Third, based on a time-delay principle and Lyapunov stability theory, a co-design method is proposed to obtain the event generator and the fuzzy controller simultaneously. The proposed event-triggered fuzzy control method is effective to improve performances of the suspension system and guarantee the limits of suspension travel and tire deflection. Finally, compared with the existing method, the effectiveness of the proposed method is verified by simulation tests with various road disturbances.

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Neuro-Adaptive Fault-Tolerant Approach for Active Suspension Control of High-Speed Trains

Cited by 30 publications

References 30 publications

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

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

Design of an adaptive neuro-observer-based feedback controller for high-speed trains with parametric uncertainties

Event-triggered fuzzy control for vehicle nonlinear suspension systems with time delay

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