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Volume 6 Issue 2
Mar.  2019

IEEE/CAA Journal of Automatica Sinica

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Xiaolong Chen, Han Zhao, Shengchao Zhen and Hao Sun, "Adaptive Robust Control for a Lower Limbs Rehabilitation Robot Running Under Passive Training Mode," IEEE/CAA J. Autom. Sinica, vol. 6, no. 2, pp. 493-502, Mar. 2019. doi: 10.1109/JAS.2019.1911402
Citation: Xiaolong Chen, Han Zhao, Shengchao Zhen and Hao Sun, "Adaptive Robust Control for a Lower Limbs Rehabilitation Robot Running Under Passive Training Mode," IEEE/CAA J. Autom. Sinica, vol. 6, no. 2, pp. 493-502, Mar. 2019. doi: 10.1109/JAS.2019.1911402

Adaptive Robust Control for a Lower Limbs Rehabilitation Robot Running Under Passive Training Mode

doi: 10.1109/JAS.2019.1911402

the National Natural Science Foundation of China 51505116

the Fundamental Research Funds for the Central Universities JZ2016HGTB0716

Natural and Science Foundation of Anhui Province 1508085SME221

China Postdoctoral Science Foundation 2016M590563

the Science and Technology Public Relations Project of Anhui Province 1604a0902181

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  • This paper focuses on the problem of the adaptive robust control of a lower limbs rehabilitation robot (LLRR) that is a nonlinear system running under passive training mode. In reality, uncertainties including modeling error, initial condition deviation, friction force and other unknown external disturbances always exist in a LLRR system. So, it is necessary to consider the uncertainties in the unilateral man-machine dynamical model of the LLRR we described. In the dynamical model, uncertainties are (possibly fast) time-varying and bounded. However, the bounds are unknown. Based on the dynamical model, we design an adaptive robust control with an adaptive law that is leakage type based and on the framework of Udwadia-Kalaba theory to compensate for the uncertainties and to realize tracking control of the LLRR. Furthermore, the effectiveness of designed control is shown with numerical simulations.


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