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Yuexuan Xu,Xin Guo,Bokai Xuan,Hao Sun,Gaowei Zhang,Jian Li,Xingyu Huo,Zhifeng Gu 제어·로봇·시스템학회 2024 International Journal of Control, Automation, and Vol.22 No.3
This paper investigates an impedance-based iterative learning sliding mode control scheme for robotassisted bathing, taking into consideration scenarios with unknown model parameters. Initially, the utilization ofimpedance control is not confined to merely adjusting the desired trajectory but is also instrumental in ensuringactive compliance control during the robot-assisted bathing procedure. Furthermore, an iterative learning control(ILC) is devised to estimate the iteration-invariant dynamic parameters, which are intricate and challenging to precisely ascertain in practical applications. To mitigate the effect of divergent initial conditions in ILC, a trajectoryreconstruction method is introduced, thus ensuring the convergence of tracking errors even when starting from random initial states. Moreover, an adaptive sliding mode control mechanism is proposed to counteract non-parametricexternal disturbances and the torque generated through human-machine interaction during the bathing process. Theconvergence of the double closed-loop system in both the time and iterative domains is demonstrated through theapplication of the composite energy function method. Eventually, the efficacy and superiority of the control strategyoutlined in this paper are jointly verified through co-simulation employing MATLAB and ADAMS.
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