Active torque-based gait adjustment multi-level control strategy for lower limb patient–exoskeleton coupling system in rehabilitation training

Yu Wang, Yang Tian, Yida Guo and Haoping Wang

Mathematics and Computers in Simulation (MATCOM), 2024, vol. 215, issue C, 357-381

Abstract: This paper proposes an active torque-based gait adjustment multi-level control strategy for lower limb patient–exoskeleton coupling system (LLPECS) in rehabilitation training. The proposed controller has three levels of high, middle, and low sub-controllers: gait adjustment layer (high-level), interaction torque design layer (middle-level), and trajectory tracking layer (low-level). The high-level sub-controller uses an adaptive central pattern generator (ACPG) to adjust the desired gait for rehabilitation training according to the patient’s active torque. In the middle-level sub-controller, the desired interaction torque is designed with neural networks and the estimated muscle torque by utilizing nonlinear disturbance observer (NDO). In the low-level sub-controller, a time delay estimation-based prescribed performance model free control is designed for the accurate tracking performance of the exoskeleton, so as to make the actual interaction torque track the desired value. An exoskeleton virtual prototype, which is developed in SolidWorks, has been imported to MATLAB/Simulink to conduct co-simulations in the SimMechanics environment. The results of co-simulations demonstrate the effectiveness of the proposed control strategy when the patient’s muscle torque is at different recovery degrees.

Keywords: Adaptive central pattern generator; Lower limb rehabilitation exoskeleton; Nonlinear disturbance observer; Model free control; Prescribed performance control (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:215:y:2024:i:c:p:357-381

DOI: 10.1016/j.matcom.2023.08.020

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