Abstract
For flexible joint (FJ) robotic systems with uncertainties, a command filter based backstepping control is proposed in this paper. Through the control scheme, an adaptive controller is constructed to track desired position. In order to overcome complex computation problem in backstepping technology, a command filter is used, and the filtering error compensation is further defined. To deal with the uncertain dynamics of flexible joint robot system, the neural network approximation technology is adopted. The simulation results of FJ robot are given to show the effectiveness.
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References
Rodriguez-Angeles A (2004) Mutual synchronization of robots via estimated state feedback: a cooperative approach. IEEE Trans Control Syst Technol 12(4):542–554
Nuno G, Ortega R, Basanez L, Hill D (2011) Synchronization of networks of nonidentical EulerCLagrange systems with uncertain parameters and communication delays. IEEE Trans Autom Control 56(4):935–941
Hl W (2016) Consensus of networked mechanical systems with communication delays: a unified framework. IEEE Trans Autom Control 59(6):1571–1576
Nanos K, Papadopoulos EG (2015) On the dynamics and control of flexible joint space manipulators. Control Eng Pract 45:230–243
Yoo SJ, Park JB, Choi YH (2008) Adaptive output feedback control of flexible-joint robots using neural networks: dynamic surface design approach. IEEE Trans Neural Netw 19(10):1712–1726
Yoo SJ (2014) Distributed adaptive containment control of networked flexible-joint. Expert Syst Appl 41(2):470–477
Farrell JA, Polycarpou M, Sharma M et al (2009) Command filtered backstepping. IEEE Trans Autom Control 54(6):1391–1395
Dong WJ, Marios M et al (2012) Command filtered adaptive backstepping. IEEE Trans Control Syst Technol 20(3):566–580
Zhao L, Yu JP, Yu HS et al (2019) Neuroadaptive containment control of nonlinear multi-agent systems with input saturations. Int J Robust Nonlinear Control 29(9):2742–2756
Zhao L, Yu JP, Lin C (2019) Distributed adaptive output consensus tracking of nonlinear multi-agent systems via state observer and command filtered backstepping. Inf Sci 478:355–374
Jia YM (2003) Robust control with decoupling performance for steering and traction of 4WS vehicles under velocity-varying motion. IEEE Trans Control Syst Tech 8(3):554–569
Zhao L, Yu JP, Yu HS (2018) Adaptive finite-time attitude tracking control for spacecraft with disturbances. IEEE Trans Aerosp Electron Syst 54(3):1297–1305
Zhao L, Yu JP, Lin C (2018) Adaptive neural consensus tracking for nonlinear multi-agent systems using finite-time command filtered backstepping. IEEE Trans Sys Man Cybern: Syst 48(11):2003–2012
Acknowledgements
This work was supported by the National Natural Science Foundation of China (61603204, 61573204), and the Shandong Province Outstanding Youth Fund (ZR2018JL020).
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Wang, D., Zhao, L., Yu, J. (2020). Neural Network Based Adaptive Backstepping Control of Uncertain Flexible Joint Robot Systems. In: Jia, Y., Du, J., Zhang, W. (eds) Proceedings of 2019 Chinese Intelligent Systems Conference. CISC 2019. Lecture Notes in Electrical Engineering, vol 592. Springer, Singapore. https://doi.org/10.1007/978-981-32-9682-4_40
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DOI: https://doi.org/10.1007/978-981-32-9682-4_40
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Online ISBN: 978-981-32-9682-4
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