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Article

Adaptive Sliding Mode Neural Network Control and Flexible Vibration Suppression of a Flexible Spatial Parallel Robot

1
School of Computer Science and Engineering, Tianjin University of Technology, Tianjin 300384, China
2
Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control, National Demonstration Center for Experimental Mechanical and Electrical Engineering Education, Tianjin University of Technology, Tianjin 300384, China
*
Author to whom correspondence should be addressed.
Electronics 2021, 10(2), 212; https://doi.org/10.3390/electronics10020212
Received: 4 December 2020 / Revised: 15 January 2021 / Accepted: 15 January 2021 / Published: 18 January 2021
With the goal of creating a flexible spatial parallel robot system in which the elastic deformation of the flexible link causes a rigid moving platform to produce small vibrations, we proposed an adaptive sliding mode control algorithm based on a neural network. To improve the calculation efficiency, the finite element method was used to discretize the flexible spatial link, and then the displacement field of the flexible spatial link was described based on floating frame of reference coordinates, and the dynamic differential equation of the flexible spatial link considering high-frequency vibrations was established through the Lagrange equation. This was combined with the dynamic equation of the rigid link and the dynamic equation considering small displacements of the rigid movable platform due to elastic deformation, and a highly nonlinear and accurate dynamic model with a rigid–flexible coupling effect was obtained. Based on the established accurate multi-body dynamics model, the driving torque with coupling effects was calculated in advance for feedforward compensation, and the adaptive sliding mode controller was used to improve the tracking performance of the system. The nonlinear error was examined to determine the performance of the neural network’s approximation of the nonlinear system. The trajectory errors of the moving platform in the X-, Y-, and Z-directions were reduced by 12.1%, 38.8%, and 50.34%, respectively. The results showed that the designed adaptive sliding mode neural network control met the control accuracy requirements, and suppressed the vibrations generated by the deformation of the flexible spatial link. View Full-Text
Keywords: flexible spatial parallel robot; control algorithm; neural network; dynamics flexible spatial parallel robot; control algorithm; neural network; dynamics
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MDPI and ACS Style

Zhang, Q.; Zhao, X.; Liu, L.; Dai, T. Adaptive Sliding Mode Neural Network Control and Flexible Vibration Suppression of a Flexible Spatial Parallel Robot. Electronics 2021, 10, 212. https://doi.org/10.3390/electronics10020212

AMA Style

Zhang Q, Zhao X, Liu L, Dai T. Adaptive Sliding Mode Neural Network Control and Flexible Vibration Suppression of a Flexible Spatial Parallel Robot. Electronics. 2021; 10(2):212. https://doi.org/10.3390/electronics10020212

Chicago/Turabian Style

Zhang, Qingyun, Xinhua Zhao, Liang Liu, and Tengda Dai. 2021. "Adaptive Sliding Mode Neural Network Control and Flexible Vibration Suppression of a Flexible Spatial Parallel Robot" Electronics 10, no. 2: 212. https://doi.org/10.3390/electronics10020212

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