Robust consensus braking algorithm for distributed EMUs with uncertainties

He, Jinghan; Yang, Buchong; Zhang, Changfan; Liu, Jianhua; Mao, Songan; Shi, Laicheng; Cheng, Xiang

doi:10.1049/iet-cta.2018.6107

Cited by 7 publications

(6 citation statements)

References 22 publications

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“…Figures 3c and 4c show the relative displacement curve of each carriage under this condition. It can be seen that the relative displacement of adjacent carriages is kept within the range of [9, 11] during braking, which meets the safety constraint requirements of the coupler force between adjacent urban rail carriages.…”

Section: Simulation Resultsmentioning

confidence: 73%

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Cooperative braking of urban rail vehicles with Koopman model predictive control

Gao

Peng

et al. 2022

IET Control Theory & Appl

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Braking control of urban rail vehicles with multiple carriages is critical to ensure the safe operation of urban rails. However, existing decentralized braking control methods lead to the inconsistent speed and excessive coupler force among carriages, which compromises the operation safety of urban rails. To address this issue, a cooperative braking strategy is proposed for urban rail vehicles based on Koopman model predictive control method. First, a cyber‐physical model is established, where the physical layer characterizes the dynamic model of multiple carriages using the Koopman operator. The cyber layer represents the communication topology of carriages with graph theory. Second, a cooperative braking controller is designed with the distributed model predictive control method. An optimisation problem is formulated to minimize the speed inconsistency and relative displacement difference among carriages. Third, extensive simulations under various scenarios, including normal and extreme operating conditions, are conducted to verify the effectiveness of the proposed method. Simulation results show that, compared with the classical decentralized method, the proposed braking method reduces the average relative displacement by 78% while reducing the speed error by 29%.

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Section: Simulation Resultsmentioning

confidence: 73%

“…In the multimass point model, each carriage of the vehicle is modelled as a mass point connected with elastic couplers, which can represent the coupler force through the relative displacement between carriages [10]. The multi-mass point model has been applied in both cruise control and braking control of rail vehicles [11,12].…”

Section: Introductionmentioning

confidence: 99%

Cooperative braking of urban rail vehicles with Koopman model predictive control

Gao

Peng

et al. 2022

IET Control Theory & Appl

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“…For the switching subsystem f 2 (x 12 , t), just design the appropriate sliding-mode coefficient K 1 > p 1 + η 1 that can obtain formula (27) in the same way; that is, the uniaxial error e 1 of the switching subsystem f 2 (x 12 , t) gradually converges to 0. e common Lyapunov function shows that _ V 1 exists regardless of the subsystem activated. us, the sliding-mode function s 1 ≠ 0 is attenuated.…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

“…To sum up, the scholars performed substantial research on multimotor synchronous control [27,28]. However, the results in switching synchronous control are rare, especially for the study of motor load torque abrupt change which has always been the least of concern.…”

Section: Introductionmentioning

confidence: 99%

Multimotor Improved Relative Coupling Cooperative Control Based on Sliding-Mode Controller

Zhang

Ming-jie

2020

Mathematical Problems in Engineering

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To provide cooperative control under complex working conditions of a filling multimotor system, this paper proposes a relative coupling control strategy with a switching system structure. Firstly, a multistation transmission system composed of a filling motor and a transfer motor is designed according to different filling processes. Secondly, a stable sliding-mode surface common to the multimotor system is selected, and an equivalent sliding-mode controller corresponding to each motor is designed. Thirdly, public Lyapunov stability theory is used to prove that the switched system can move from any initial state to the common sliding surface of the system, thereby ensuring the asymptotic stability of the entire system. Simulation results show that this method has a more significant control effect on the system error of each motor in comparison with the traditional relative coupling control structure.

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“…During operation, HHTs receive various forces through a coupler system, including basic resistance, additional resistance and the coupler forces of adjacent carriages. 28 Therefore, on the basis of the analysis of train coupling and uncertain disturbance forces, a train dynamic model composed of n carriages is designed as follows 29…”

Section: Dynamic Model Descriptionmentioning

confidence: 99%

Tracking control via sliding mode for heavy-haul trains with input saturation

Yang

Zhang

et al. 2020

Measurement and Control

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To address the tracking control problem of heavy-haul trains (HHTs) with input saturation during operation, an anti-saturation sliding mode (SMES) control method based on dynamic auxiliary compensator (DAC) is presented. Firstly, an HHT model with nonlinear coupling and uncertain disturbances is built. Secondly, a new type of DAC is introduced to overcome the difficulty of traditional dynamic auxiliary compensator (TDAC) with a large upper bound on the compensation signal. Finally, an anti-saturation SMES control algorithm is designed to reduce the influence of input saturation on the tracking accuracy of each carriage. Simulation results verify the effectiveness of the algorithm in terms of tracking accuracy, anti-interference, and anti-saturation.

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Robust consensus braking algorithm for distributed EMUs with uncertainties

Cited by 7 publications

References 22 publications

Cooperative braking of urban rail vehicles with Koopman model predictive control

Cooperative braking of urban rail vehicles with Koopman model predictive control

Multimotor Improved Relative Coupling Cooperative Control Based on Sliding-Mode Controller

Tracking control via sliding mode for heavy-haul trains with input saturation

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