Deformation Estimator Network-Based Feedback Control for Wearable Exoskeleton With Body Disturbances: Toward Stable and Dynamic Walking
提出一种TDE-BVC反馈控制方法，利用变压器变形估计网络和仿生粘弹性顺应性，使外骨骼在人体扰动下实现稳定动态行走，实验验证了有效性。
Accurately estimating uncertain body disturbances is critical for the effective integration of wearable exoskeletons for active human users. In this article, considering nonlinear time-varying human disturbances, we propose a TDE-BVC feedback control method that performs biomimetic viscoelastic compliance (BVC) with transformer-based deformation estimator (TDE). The method provides human-exoskeleton with stable and dynamic walking capabilities. We developed a transformer-based end-to-end deformation estimation sequence network that simultaneously captures the mapping relationship between foot force/torque and exoskeleton deformation. Moreover, we integrated the BVC to eliminate the impact and external disturbances experienced by the human-exoskeleton, enabling it to closely follow a reference gait, and utilized Lyapunov’s theorem to prove its stability. The control strategy is independent of the parameters of the human exoskeleton. To evaluate the effectiveness of the proposed method, walking experiments were conducted on different subjects. Our results indicate that with only 6-axis force/torque sensors, the TDE-BVC controller could accurately estimate and compensate for the deformation of different human-exoskeletons in each control cycle <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$(p\lt 0.001)$ </tex-math></inline-formula>, with robustly stable and adaptive dynamic walking within a bounded control error.