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Gaussian process dynamic modeling and backstepping sliding mode control for magnetic levitation system of maglev train

100%

Sun Y. , Wang S. , Lu Y. , Xu J.

Journal of Theoretical and Applied Mechanics

2022

tom Vol. 60 nr 1

49--62

The maglev trains are strongly nonlinear and open-loop unstable systems with external disturbances and parameters uncertainty. In this paper, the Gaussian process method is utilized to get the dynamic parameters, and a backstepping sliding mode controller is proposed for magnetic levitation systems (MLS) of maglev trains. That is, for a MLS of a maglev train, a nonlinear dynamic model with accurate parameters is obtained by the Gaussian process regression method, based on which a novel robust control algorithm is designed. Specifically, the MLS is divided into two sub-systems by a backstepping method. The inter virtual control inputs and the Lyapunov function are constructed in the first sub-system. For the second sub-system, the sliding mode surface is constructed to fulfil the design of the whole controller to asymptotically regulate the airgap to a desired trajectory. The stability of the proposed control method is analyzed by the Lyapunov method. Both simulation and experimental results are included to illustrate the superior performance of the presented method to cope with parameters perturbations and external disturbance.

Mechanism of micro/nano-bubble formation and cavitation effect on bubbles size distribution in flotation

100%

Deng X. , Lv B. , Cheng G. , Lu Y.

tom Vol. 56, iss. 3

504--512

In this study, micro/nano-bubble generated by cavitation effect as a promoting factor for flotation was investigated using the atomic force microscope (AFM). Hydrodynamic cavitation tests were performed with a venturi bubble generator. Additionally, bubble size distribution (BSD) under the hydrodynamic cavitation effect was also studied at different water flow speed conditions. Dozens of nanometers height bubbles attached to the hydrophobic substrates were detected. Besides, the cavitation cloud grew thicker with the flow velocity increasing from 26.52 m/sec to 53.04 m/sec, near the venturi tube nozzle. All results showed the importance of the cavitation effect on the micro/nano-bubbles formation and the BSD in flotation.

Fault detection for DFIG based on sliding mode observer of new reaching law

75%

Li R. , Yu W. , Wang J. , Lu Y. , Jiang D. , Zhong G. , Zhou Z.

Bulletin of the Polish Academy of Sciences. Technical Sciences

2021

tom Vol. 69, nr 3

art. no. e137389

For fault detection of doubly-fed induction generator (DFIG), in this paper, a method of sliding mode observer (SMO) based on a new reaching law (NRL) is proposed. The SMO based on the NRL (NRL- SMO) theoretically eliminates system chatter caused by the reaching law and can be switched in time with system interference in terms of robustness and smoothness. In addition, the sliding mode control law is used as the index of fault detection. Firstly, this paper gives the NRL with the theoretically analyzes. Secondly, according to the mathematical model of DFIG, NRL-SMO is designed, and its analysis of stability and robustness are carried out. Then this paper describes how to choose the optimal parameters of the NRL-SMO. Finally, three common wind turbine system faults are given, which are DFIG inter-turn stator fault, grid voltage drop fault, and rotor current sensor fault. The simulation models of the DFIG under different faults is established. The simulation results prove that the superiority of the method of NRL-SMO in state tracking and the feasibility of fault detection.