LI, Wending ;SHI, Guanglin ;ZHAO, Chun ;LIU, Hongyu ;FU, Junyong . RBF Neural Network Sliding Mode Control Method Based on Backstepping for an Electro-hydraulic Actuator. Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 66, n.12, p. 697-708, december 2020. ISSN 0039-2480. Available at: <https://www.sv-jme.eu/article/rbf-neural-network-sliding-mode-control-method-based-on-backstepping-for-electro-hydraulic-actuator/>. Date accessed: 19 nov. 2024. doi:http://dx.doi.org/10.5545/sv-jme.2020.6866.
Li, W., Shi, G., Zhao, C., Liu, H., & Fu, J. (2020). RBF Neural Network Sliding Mode Control Method Based on Backstepping for an Electro-hydraulic Actuator. Strojniški vestnik - Journal of Mechanical Engineering, 66(12), 697-708. doi:http://dx.doi.org/10.5545/sv-jme.2020.6866
@article{sv-jmesv-jme.2020.6866,
author = {Wending Li and Guanglin Shi and Chun Zhao and Hongyu Liu and Junyong Fu},
title = {RBF Neural Network Sliding Mode Control Method Based on Backstepping for an Electro-hydraulic Actuator},
journal = {Strojniški vestnik - Journal of Mechanical Engineering},
volume = {66},
number = {12},
year = {2020},
keywords = {RBF neural network, sliding mode, backstepping, non-linear control, electro-hydraulic actuator},
abstract = {Aiming at the interference problem and the difficulty of model parameter determination caused by the nonlinearity of the valve-controlled hydraulic cylinder position servo system, this study proposes a radial basis function (RBF) neural network sliding mode control strategy based on a backstepping strategy for the electro-hydraulic actuator. First, the non-linear system model of the third-order position electro-hydraulic control servo system is established on the basis of the principle analysis. Second, the model function RBF adaptive law and backstepping control law are designed according to Lyapunov’s stability theorem to solve the problem of external load disturbance and modelling uncertainty, combined with sliding mode control strategy and virtual control law. Finally, simulation and experiment on MATLAB Simulink and semi-physical experimental platform are accomplished to show the effectiveness of the proposed method. Moreover, results show that the designed controller has high tracking accuracy to the given signal.},
issn = {0039-2480}, pages = {697-708}, doi = {10.5545/sv-jme.2020.6866},
url = {https://www.sv-jme.eu/article/rbf-neural-network-sliding-mode-control-method-based-on-backstepping-for-electro-hydraulic-actuator/}
}
Li, W.,Shi, G.,Zhao, C.,Liu, H.,Fu, J. 2020 December 66. RBF Neural Network Sliding Mode Control Method Based on Backstepping for an Electro-hydraulic Actuator. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 66:12
%A Li, Wending %A Shi, Guanglin %A Zhao, Chun %A Liu, Hongyu %A Fu, Junyong %D 2020 %T RBF Neural Network Sliding Mode Control Method Based on Backstepping for an Electro-hydraulic Actuator %B 2020 %9 RBF neural network, sliding mode, backstepping, non-linear control, electro-hydraulic actuator %! RBF Neural Network Sliding Mode Control Method Based on Backstepping for an Electro-hydraulic Actuator %K RBF neural network, sliding mode, backstepping, non-linear control, electro-hydraulic actuator %X Aiming at the interference problem and the difficulty of model parameter determination caused by the nonlinearity of the valve-controlled hydraulic cylinder position servo system, this study proposes a radial basis function (RBF) neural network sliding mode control strategy based on a backstepping strategy for the electro-hydraulic actuator. First, the non-linear system model of the third-order position electro-hydraulic control servo system is established on the basis of the principle analysis. Second, the model function RBF adaptive law and backstepping control law are designed according to Lyapunov’s stability theorem to solve the problem of external load disturbance and modelling uncertainty, combined with sliding mode control strategy and virtual control law. Finally, simulation and experiment on MATLAB Simulink and semi-physical experimental platform are accomplished to show the effectiveness of the proposed method. Moreover, results show that the designed controller has high tracking accuracy to the given signal. %U https://www.sv-jme.eu/article/rbf-neural-network-sliding-mode-control-method-based-on-backstepping-for-electro-hydraulic-actuator/ %0 Journal Article %R 10.5545/sv-jme.2020.6866 %& 697 %P 12 %J Strojniški vestnik - Journal of Mechanical Engineering %V 66 %N 12 %@ 0039-2480 %8 2020-12-23 %7 2020-12-23
Li, Wending, Guanglin Shi, Chun Zhao, Hongyu Liu, & Junyong Fu. "RBF Neural Network Sliding Mode Control Method Based on Backstepping for an Electro-hydraulic Actuator." Strojniški vestnik - Journal of Mechanical Engineering [Online], 66.12 (2020): 697-708. Web. 19 Nov. 2024
TY - JOUR AU - Li, Wending AU - Shi, Guanglin AU - Zhao, Chun AU - Liu, Hongyu AU - Fu, Junyong PY - 2020 TI - RBF Neural Network Sliding Mode Control Method Based on Backstepping for an Electro-hydraulic Actuator JF - Strojniški vestnik - Journal of Mechanical Engineering DO - 10.5545/sv-jme.2020.6866 KW - RBF neural network, sliding mode, backstepping, non-linear control, electro-hydraulic actuator N2 - Aiming at the interference problem and the difficulty of model parameter determination caused by the nonlinearity of the valve-controlled hydraulic cylinder position servo system, this study proposes a radial basis function (RBF) neural network sliding mode control strategy based on a backstepping strategy for the electro-hydraulic actuator. First, the non-linear system model of the third-order position electro-hydraulic control servo system is established on the basis of the principle analysis. Second, the model function RBF adaptive law and backstepping control law are designed according to Lyapunov’s stability theorem to solve the problem of external load disturbance and modelling uncertainty, combined with sliding mode control strategy and virtual control law. Finally, simulation and experiment on MATLAB Simulink and semi-physical experimental platform are accomplished to show the effectiveness of the proposed method. Moreover, results show that the designed controller has high tracking accuracy to the given signal. UR - https://www.sv-jme.eu/article/rbf-neural-network-sliding-mode-control-method-based-on-backstepping-for-electro-hydraulic-actuator/
@article{{sv-jme}{sv-jme.2020.6866},
author = {Li, W., Shi, G., Zhao, C., Liu, H., Fu, J.},
title = {RBF Neural Network Sliding Mode Control Method Based on Backstepping for an Electro-hydraulic Actuator},
journal = {Strojniški vestnik - Journal of Mechanical Engineering},
volume = {66},
number = {12},
year = {2020},
doi = {10.5545/sv-jme.2020.6866},
url = {https://www.sv-jme.eu/article/rbf-neural-network-sliding-mode-control-method-based-on-backstepping-for-electro-hydraulic-actuator/}
}
TY - JOUR AU - Li, Wending AU - Shi, Guanglin AU - Zhao, Chun AU - Liu, Hongyu AU - Fu, Junyong PY - 2020/12/23 TI - RBF Neural Network Sliding Mode Control Method Based on Backstepping for an Electro-hydraulic Actuator JF - Strojniški vestnik - Journal of Mechanical Engineering; Vol 66, No 12 (2020): Strojniški vestnik - Journal of Mechanical Engineering DO - 10.5545/sv-jme.2020.6866 KW - RBF neural network, sliding mode, backstepping, non-linear control, electro-hydraulic actuator N2 - Aiming at the interference problem and the difficulty of model parameter determination caused by the nonlinearity of the valve-controlled hydraulic cylinder position servo system, this study proposes a radial basis function (RBF) neural network sliding mode control strategy based on a backstepping strategy for the electro-hydraulic actuator. First, the non-linear system model of the third-order position electro-hydraulic control servo system is established on the basis of the principle analysis. Second, the model function RBF adaptive law and backstepping control law are designed according to Lyapunov’s stability theorem to solve the problem of external load disturbance and modelling uncertainty, combined with sliding mode control strategy and virtual control law. Finally, simulation and experiment on MATLAB Simulink and semi-physical experimental platform are accomplished to show the effectiveness of the proposed method. Moreover, results show that the designed controller has high tracking accuracy to the given signal. UR - https://www.sv-jme.eu/article/rbf-neural-network-sliding-mode-control-method-based-on-backstepping-for-electro-hydraulic-actuator/
Li, Wending, Shi, Guanglin, Zhao, Chun, Liu, Hongyu, AND Fu, Junyong. "RBF Neural Network Sliding Mode Control Method Based on Backstepping for an Electro-hydraulic Actuator" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 66 Number 12 (23 December 2020)
Strojniški vestnik - Journal of Mechanical Engineering 66(2020)12, 697-708
© The Authors, CC-BY 4.0 Int. Change in copyright policy from 2022, Jan 1st.
Aiming at the interference problem and the difficulty of model parameter determination caused by the nonlinearity of the valve-controlled hydraulic cylinder position servo system, this study proposes a radial basis function (RBF) neural network sliding mode control strategy based on a backstepping strategy for the electro-hydraulic actuator. First, the non-linear system model of the third-order position electro-hydraulic control servo system is established on the basis of the principle analysis. Second, the model function RBF adaptive law and backstepping control law are designed according to Lyapunov’s stability theorem to solve the problem of external load disturbance and modelling uncertainty, combined with sliding mode control strategy and virtual control law. Finally, simulation and experiment on MATLAB Simulink and semi-physical experimental platform are accomplished to show the effectiveness of the proposed method. Moreover, results show that the designed controller has high tracking accuracy to the given signal.