Abstract
A decentralized robust control algorithm for robotic manipulator in joint space is proposed, in which the linkage and its joint driver are treated as a module with a torque sensor installed on its driver shaft connecting the successive module. Due to the coupling between two connected dynamic modules can be measured by the torque sensor, the computation of the nonlinear coupling effect caused by the rest upper linkages is no longer needed, which means the complexity of the dynamic equations of the manipulator will be greatly reduced and the real-time compensation calculation of manipulator dynamics is not required in its control loop. Furthermore, the joint torque sensor enables the feedback of the external disturbance and gravity load acting on the linkage, which equips the control system with a strong anti-interference capability. Since there is no need to compute the feedforward compensation joint torque, the structure of the control system becomes simple and the joint controller can be independently designed. An integral adaptive compensator is specifically designed to deal with the compensation of the dynamic coupling from the low linkages because such coupling cannot be sensed by the joint torque sensor. A robust control strategy was proposed to compensate for the friction parameter variation between the modules of the manipulator and the uncertainty caused by the reconfiguration of the manipulator. The computer simulation is conducted to verify the effectiveness of the proposed control algorithm.
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Ambar, R.B.; Sagara, S.; Imaike, K.: Experiment on a dual-arm underwater robot using resolved acceleration control method. Artif. Life Robot. 20(1), 34–41 (2015)
Zhang, D.; Wang, Z.; Tomizuka, M.: A variable parameter model-based feedforward com- pensation method for tracking control. IEEE/CAA J. Autom. Sin. 7(3), 693–701 (2020)
Paul, R.: Modeling, trajectory calculation and servoing of a computer controlled arm. Stanford University, Stanford (1972)
Yu, X.; He, W.; Li, Q.: Human-robot co-carrying using visual and force sensing. IEEE Trans. Ind. Electron. 68, 8657–8666 (2020)
Liu, A.; Zhao, H.; Song, T.: Adaptive control of manipulator based on neural network. Neural Comput. Appl. 33, 4077–4085 (2020)
Yu, X.; He, W.; Li, H.: Adaptive fuzzy full-state and output-feedback control for uncertain robots with output constraint. IEEE Trans. Syst. Man Cybern. Syst. 51, 6994–7007 (2020)
Imura, J.; Sugie, T.; Yokokohji, Y.: Robust control of robot manipulators based on joint torque sensor information. In: IEEE/RSJ International Workshop on Intelligent Robots & Systems 91 Intelligence for Mechanical Systems, IEEE (2002)
Li, Y.; Lu, Z.; Zhou, F.: Decentralized active fault tolerant control for modular and reconfigurable robot with torque sensor. In: 2019 1st International Conference on Industrial Artificial Intelligence (IAI), Shenyang, China (2019)
Asada, H.; Lim, S.K.: The joint torque feedback control of a direct-drive arm. IFAC Proc. Vol. 20(5), 227–232 (1987)
Le-Tien, L.; Albu-Schaffer, A.: Robust adaptive tracking control based on state feedback controller with integrator terms for elastic joint robots with uncertain parameters. IEEE Trans. Control Syst. Technol. 26, 2259–2267 (2017)
Liu, G.: Decomposition-based friction compensation of mechanical systems. Mechatronics 12(5), 755–769 (2002)
Cai, L.; Songag, G.: Joint stick-slip friction compensation of robot manipulators by using smooth robust controllers. J. Robot. Syst. 11(6), 451–470 (2010)
Muralidharan, M.; Mohan, S.: Task- space pose decomposition motion control of a mobile manipulator: SIGMA 2018, Vol. 1, 175–185 (2018)
Liu, T.; Lei, Y.; Han, L.; Xu, W.; Zou, H.: Coordinated resolved motion control of dual-arm manipulators with closed chain. Int. J. Adv. Robot. Syst. 13(3). https://doi.org/10.5772/6343080 (2016)
Wanmin, C.; Yongming, Li.; Shaocheng, T.: Adaptive fuzzy backstepping tracking control for flexible robotic manipulator. IEEE/CAA J. Autom. Sin. 8(12), 1923–1930 (2021)
Yin, X.; Li, P.: Direct adaptive robust tracking control for 6 DOF industrial robot with enhanced accuracy. ISA Trans. 72, 178 (2018)
Wang, Y.; Chen, X.: Manipulator of robust fuzzy adaptive compensation control. In: 2018 3rd Asia-Pacific Conference on Intelligent Robot Systems (ACIRS), (2018)
Liu, G.; Abdul, S.; Andrew, A.: Distri- buted control of modular and reconfigurable robot with torque sensing. Robotica 26(1), 75–84 (2008)
Abdul, S.: Robust and fault tolerant control of modular and reconfigurable robots. Ryerson University (Canada) (2009)
Slotine, J.; Li, W.P.: Applied nonlinear control. China Machine Press, Beijing (1991)
Wei, N.; Sun, H.; Jia, Q.: Analysis and design optimization of a compact and lightweight joint torque sensor for space manipulators. Adv. Mech. Eng. 2013(2013), 111–114 (2013)
Osypiuk, R.; Piskorowski, J.; Kubus, D.: A method of improving the dynamic re- sponse of 3D force/torque sensors. Mech. Syst. Signal Process. 68, 366–377 (2015)
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Qiao, B., Qu, H. & Deng, Y. Decentralized Robust Control of Robotic Manipulator in Joint Space Based on Torque Feedbacks. Arab J Sci Eng 48, 11277–11284 (2023). https://doi.org/10.1007/s13369-022-07381-5
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DOI: https://doi.org/10.1007/s13369-022-07381-5