Adaptive Admittance Control for Lower Limb Rehabilitation Robots with Nominal Interaction Mismatch Compensation
Year: 2026
Type: article
Abstract: Maintaining prescribed joint motion while allowing for compliant responses to changing interaction is challenging in passive lower limb rehabilitation. We propose interaction error-driven adaptive admittance control (IE-AAC), which subtracts the predicted nominal-interaction difference between reference and commanded states. A soft dead zone processes the corrected residual before bounded scheduling of virtual damping, stiffness, and interaction mapping gain. We evaluate the controller using a common reference reconstructed from simulated therapist demonstrations and a phenomenological interaction model. In 100 strictly paired Monte Carlo trials, IE-AAC reduced the equally weighted hip–knee–ankle mean reference deviation RMSE by 20.26%, 32.09%, and 28.23% relative to fixed admittance and two literature-derived variable admittance comparators (Zhang-2018 and Cao-2024), respectively. All four controllers in this comparison share mismatch compensation, so the reductions quantify differences in the implemented scheduling laws; a separate ablation evaluates compensation itself. The results include knee-specific trade-offs in tracking, smoothness, and interaction residual.
Source: Machines
Authors: Jiaqi Zhou, Yuanliang Zhang, Mingda Miao
Institution: Jiangsu Ocean University
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W7225802097
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