Backstepping-based lower limb exoskeleton control method

Abstract

The invention relates to a Backstepping-based lower limb exoskeleton control method, which comprises the following steps of: 1, establishing a lower limb exoskeleton dynamical model, and converting the lower limb exoskeleton dynamical model into a control system state equation; 2, designing a Backstepping controller, and carrying out the control of the Backstepping controller; 3, improving an RBF disturbance observer, including designing the RBF disturbance observer and an RBF neural network adaptive law; and 4, performing control implementation, and enabling the lower limb exoskeleton to move according to the expected track. According to the method, for external random disturbance, the approximation characteristic of an RBF neural network is utilized, a disturbance observer is designed, and the external random disturbance is approximated; and aiming at the network approximation error existing in the RBF neural network, the disturbance observer is further improved, and the auxiliary variable is introduced to compensate the network approximation error, so that the external random disturbance is compensated, the approximation of the external random disturbance is closer to a real value, and the approximation error of the RBF neural network is reduced.

Description

technical field [0001] The invention belongs to the technical field of exoskeleton control, and in particular relates to a lower limb exoskeleton control method based on Backstepping. Background technique [0002] While providing support and protection to the human body, the exoskeleton can complete tasks that the human body cannot do alone according to the subjective wishes of the human body. The research purpose of the lower extremity exoskeleton is to enhance the physical strength of the human body and expand the walking ability of the lower limbs of the human body. It has very broad application prospects in both military and civilian fields. [0003] Since the lower extremity exoskeleton system is a typical nonlinear control system, and the Backstepping control algorithm shows superiority in controlling the nonlinear system, the application of the Backstepping control algorithm to control the lower extremity exoskeleton system can ensure the control accuracy. When the e...

AI Technical Summary

Problems solved by technology

However, due to the approximation error of the RBF neural network, it will affect the accuracy of the disturbance approximation, and then affect the tracking effect of the joint angle

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