Abstract
In order to overcome the nonlinear characteristics, parameter uncertainties and load disturbance of the hydraulic manipulator system, Firstly the driving principle and dynamics of the hydraulic manipulator are analyzed, and the nonlinear mathematical model of the servo hydraulic system in the manipulator is established, then a control strategy of indirect adaptive fuzzy sliding mode (IAFSMC) is proposed. The adaptive algorithm and the principle of fuzzy approximation is used to estimate the unknown parameters of the system, which effectively overcomes the influence of system uncertainties. By using the adaptive fuzzy control method, the switching term in the sliding mode controller achieves fuzzy approximation, which makes the switching term continuous and can effectively reduce chattering and suppress interference. Then the control law and adaptive law of the system are presented, and the stability of the algorithm is analyzed by Lyapunov method. The MATLAB is used to simulate the hydraulic servo system of the manipulator. The simulation results show that the indirect adaptive fuzzy sliding mode variable structure control method can accurately track the joint path of the hydraulic mechanical manipulator and has strong robustness to parameter changes. Compared with the traditional PID control technology, this control algorithm produces less tracking error and better control performance.
This project is supported by The Key Research Project of Shandong Province (2017CXGC0917) and The Fundamental Research Funds of Shandong University (2017JC041).
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References
Liu, H., et al.: Study on modeling and simulation of the hydraulic system of the concrete pump truck’s arms. J. Eng. Des. 17(04), 253–257+277 (2010)
Luo, Z., et al.: Kinematics and working space analysis of hydraulic manipulator based on rotary vane actuator joint. Modul. Mach. Tool Autom. Manuf. Tech. (02), 19–22 (2019)
Xu, B., Pandian, S.R., Sakagami, N., et al.: Neuro-fuzzy control of underwater vehicle-manipulator systems. J. Franklin Inst. Eng. Appl. Math. 349(3), 1125–1138 (2012)
Xu, Y., et al.: Modeling and trajectory tracking control of vehicle hydraulic rigid-flexible manipulator based on the expected joint angle compensation. J. Jilin Univ. (Eng. Technol. Ed.) 43(05), 1367–1374 (2013)
Pan, R., Du, W.: Co-simulation of adaptive fuzzy sliding mode control for crane. Chin. Hydraul. Pneum. 10(16), 92–99 (2018)
Yang, J., Tong, Z., Wang, R., et al.: Exploring fuzzy PID control of electro-hydraulic proportional system of hydraulic manipulator. Mech. Sci. Technol. Aerosp. Eng. 32(6), 834–838 (2013)
Li, Y., et al.: Adaptive second order sliding mode control for hydraulic manipulator based on backstepping. J. Jilin Univ. (Eng. Technol. Ed.) 1(45) (2015)
Mohanty, A., Yao, B.: Indirect adaptive robust control of hydraulic manipulators with accurate parameter estimates. IEEE Trans. Control Syst. Technol. 19(3), 567–575 (2011)
Liu, J.: Research on trajectory tracking and vibration suppression method of vehicle hydraulic flexible manipulator. Changchun University of Technology (2018)
Liang, X.: Research on kinematics analysis and trajectory tracking control method of redundant hydraulic mechanical arm of rescue robot. Shandong University (2018)
Bo, Y., et al.: Tracking control of hydraulic flexible manipulator motion trajectory based on neural network. Hydraul. Pneum. (10), 58–62 (2017)
Cai, Z.: Robotics, 2nd edn. Tsinghua University Press, Beijing (2009)
Guo, Q., et al.: Parametric adaptive estimation and backstepping control of electro-hydraulic actuator with decayed memory filter. ISA Trans. 62, 202–214 (2016)
Li, L., Xie, J., Huang, J.: Modeling and dynamic surface adaptive sliding mode control of erecting mechanism. Syst. Eng. Electron. 36(2), 337–342 (2014)
Liu, J.: Sliding Mode Control Design and Matlab Simulation. Tsinghua University Press, Beijing (2015)
Wang, L.: Fuzzy System and Fuzzy Control Engineering. Tsinghua University Press, Beijing (2003)
Wang, J., et al.: Indirect adaptive fuzzy sliding mode control: part I: fuzzy switching. Fuzzy Sets Syst. 122(1), 21–30 (2001)
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Huang, X., Wan, Y., Sun, Y., Hou, J. (2020). Indirect Adaptive Fuzzy Sliding-Mode Control for Hydraulic Manipulators. In: Tan, J. (eds) Advances in Mechanical Design. ICMD 2019. Mechanisms and Machine Science, vol 77. Springer, Singapore. https://doi.org/10.1007/978-981-32-9941-2_20
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DOI: https://doi.org/10.1007/978-981-32-9941-2_20
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