Adaptive Control Method of Lower Limb Exoskeleton Based on Myoelectric Prediction Model

• Published in: Zhengzhou Daxue Xuebao. Gongxue Ban = Journal of Zhengzhou University. Engineering Science Vol. 46; no. 3; p. 34
• Main Authors: Sun, Guoan, Zhao, Ming, Zhang, Tingfeng, Zhang, Bi
• Format: Journal Article
• Language: Chinese; English
• Published: Zhengzhou Zhengzhou University 01.01.2025
• Subjects: Adaptive control; Adaptive systems; Control methods; Controllers; Electromyography; Exoskeletons; Joints (anatomy); Muscles; Myoelectricity; Prediction models; Proportional integral derivative; Rehabilitation robots; Sliding mode control; Tracking; Trajectories
• ISSN: 1671-6833
• DOI: 10.13705/j.issn.1671-6833.2025.03.012

In order to improve the adaptability of lower limb rehabilitation robot, such as its difficulty to respond to the patient′s intention in real time, and to adapt to individual motion needs, in this study, an adaptive control method of lower limb exoskeleton was proposed based on myoelectric prediction model. By collecting the surface EMG signals of biceps femoris, rectus femoris and lateral femoris muscles, the EMG prediction model was constructed to predict the expected motion trajectory of patients. Aiming at the uncertainties and model errors of the system, an adaptive sliding mode controller was designed to dynamically adjust sliding mode parameters according to muscle activation, so as to improve the tracking accuracy and compliance of the robot. The myoelectric model and sliding mode controller were tested in an experiment with 5 healthy subjects. The results showed that the RMSE of the model was 7.94 for the hip joint and 9.31 for the knee joint, which could meet the need of trajectory generation. Compared with the traditional PID control, the tracking accuracy of the adaptive sliding mode controller was improved by 28%, which proved the effectiveness of the method.