Gait Planning and Multimodal Human-Exoskeleton Cooperative Control Based on Central Pattern Generator

• Published in: IEEE/ASME transactions on mechatronics Vol. 30; no. 4; pp. 2598 - 2608
• Main Authors: Kou, Jiange, Wang, Yixuan, Chen, Zhenlei, Shi, Yan, Guo, Qing
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive backstepping control; admittance control; central pattern generators (CPGs); Control methods; Cooperative control; Exoskeletons; Gait; Hip; human-exoskeleton cooperative control; lower limb exoskeleton; Modulation; Motion control; Radial basis function; Real time; Real-time systems; Switches; Tracking; Tracking errors; Training; Trajectory
• ISSN: 1083-4435; 1941-014X
• DOI: 10.1109/TMECH.2024.3453037

This study presents a multimodal human-exoskeleton cooperative control method to realize different control modes smoothly switching each other with satisfactory stable performance. Considering existed mismatch gaits of the operator comparison with the exoskeleton, the corresponding operator's gait is planned by central pattern generators (CPGs) to reduce human-exoskeleton impedance and generate real-time desired trajectory, which are used as the trajectory demand input of the exoskeleton control. Then, the admittance modulation factors is proposed to realize three motion control modes of lower limb exoskeleton, i.e., active, passive, and assist-as-needed. Meanwhile, an adaptive backstepping controller with the radial basis function neyral network estimation law is designed to guarantee the position tracking errors in uniformly ultimately boundedness under model uncertainty. Finally, the experimental studies are performed with an able-bodied operator by regulating the CPGs model parameters and modulation factors to verify the proposed multimodal human-exoskeleton cooperative control.