Neural network adaptive sliding mode control without overestimation for a maglev system

Su, Xinyi; Xu, Yujie; Yang, Xiaofeng

doi:10.1016/j.ymssp.2021.108661

Cited by 16 publications

(3 citation statements)

References 26 publications

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“…This calculation could overcome the adverse effects of system uncertainties and enhance the robustness of the system. Su et al (2022) proposed a new neural network adaptive sliding mode control method to solve the chattering problem in the control for magnetic suspension system. These suspension control technologies usually use the Taylor series expansion at the equilibrium point to linearize the system model and design controllers.…”

Section: Introductionmentioning

confidence: 99%

Dynamic model of high-speed maglev train-guideway bridge system with a nonlinear suspension controller

Bu,

Wang,

Han

et al. 2024

Advances in Structural Engineering

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To improve the anti-interference ability of maglev trains, a dynamic model of the high-speed maglev train with a nonlinear suspension controller for the guideway system is proposed in this paper. Based on the nonlinear characteristics of the magnetic suspension system, a nonlinear decoupling controller is designed using the feedback linearization theory. Then, a high-speed maglev train model is refined with a guideway coupling system, consisting of a maglev train simulated as a multi-body dynamics model with 537 degrees of freedom and a spatial finite element model of the guideway. Taking the Shanghai high-speed maglev train as an example, the correctness of the computational model is verified by comparing the modeling results with field measurement data, and the control effectiveness of the nonlinear controllers and the traditional PD controllers is compared considering different train speeds and disturbance forces. The results show that the suspension gap under the decoupling control is smaller than that under the PD control during the train operations. Under the same disturbance force, the decoupling control exhibits better control performance than the PD control. The variation amplitudes of the magnetic pole gaps are generally linearly related to the disturbance force.

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Section: Introductionmentioning

confidence: 99%

Dynamic model of high-speed maglev train-guideway bridge system with a nonlinear suspension controller

Bu,

Wang,

Han

et al. 2024

Advances in Structural Engineering

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“…by gravity. More advanced actuators can be designed from this concept, e.g., by including permanent magnets to reduce power consumption [4], [5] or a second coil to increase control possibilities [6], [7].…”

Section: Introductionmentioning

confidence: 99%

On the Stability of Electromechanical Switching Devices: An Analytic Study of Hysteretic Switching Behaviors

Ramirez-Laboreo¹,

Sagüés²

2022

Preprint

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Electromagnetic relays and solenoid actuators are commercial devices that generally exhibit bistable behavior. In fact, this is the reason why they are extensively used to switch between two possible configurations in electrical, pneumatic, or hydraulic circuits, among others. Although the state of the art is extensive on modeling, estimation, and control of these electromechanical systems, there are very few works that focus on analysis aspects. In this paper, we present an equilibrium and stability analysis whose main goal is to provide insight into such bistable behavior. The study is based on a hybrid dynamical model of the system also presented in the paper. This model is used to obtain analytic expressions that relate the physical parameters to the switching conditions. The results are extensively discussed and possible practical applications are also proposed.

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“…Because the SM control design is not affected by the system parameters and external interference of the controlled object, it has the advantages of fast response and robustness. In literature [5][6][7][8][9], the HOSM is improved to realize the application in aerospace, power system control and robot, and controlled system can achieve ideal control effect. In this article, the second order SM of supertwisting algorithm control scheme is using to achieve EPS system higher performance control.…”

Section: Introductionmentioning

confidence: 99%

Control strategy of electric power steering system based on super-twisting algorithm

Wang

He²

2022

6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022)

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With the development of new energy vehicles, the demand for auto parts is also rising. It is difficult to design the control strategy of EPS system because of multiple control objectives. In this study, a control strategy is introduced which is based on the super twisting algorithm. The control objectives are to provide ideal assist torque, respond quickly and return road information. The EPS dynamic analysis and built model in order to generate the desired motor angle. In order to achieve control objectives, the controller based on super-twisting algorithm is designed. To estimate the EPS system state and unknow inputs, the observer with unknow input is employed. Auxiliary outputs are constructed because the EPS system is not satisfied the observer-matching condition. Using of the second order SM differentiators estimate the auxiliary outputs. Finally, the performance of the controller, observer and differentiator is verified by simulation, and the controller can provide expected the assist torque. The result of simulation show that the control strategy is effectiveness and robustness.

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Neural network adaptive sliding mode control without overestimation for a maglev system

Cited by 16 publications

References 26 publications

Dynamic model of high-speed maglev train-guideway bridge system with a nonlinear suspension controller

Dynamic model of high-speed maglev train-guideway bridge system with a nonlinear suspension controller

On the Stability of Electromechanical Switching Devices: An Analytic Study of Hysteretic Switching Behaviors

Control strategy of electric power steering system based on super-twisting algorithm

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