Iterative Learning Control Method and System for Rehabilitation Mechanical Device Based on Disturbance Observer

Abstract

The invention belongs to the field of iterative learning control, in particular to an iterative learning control method and system for a rehabilitation mechanical device based on a disturbance observer. The present invention reconstructs the disturbance suffered by the rehabilitation mechanical device by using the control voltage data and the output displacement data in the repeated operation process of the rehabilitation mechanical device through the established disturbance observer, and obtains the estimated value of the total disturbance suffered by the rehabilitation mechanical device; further, using The obtained total disturbance estimate is designed based on an iterative learning controller based on a disturbance observer to repeatedly control the rehabilitation mechanical device to offset the influence of the actual disturbance; finally, the rehabilitation mechanical device obtains the ability to resist interference, and at the same time realizes that the rehabilitation mechanical device has the desired output trajectory precise tracking.

Description

technical field [0001] The invention belongs to the field of iterative learning control, in particular to an iterative learning control method and system for a rehabilitation mechanical device based on a disturbance observer. Background technique [0002] Rehabilitation mechanical devices are one of the branches of medical robots, which have received extensive research and attention in recent years. The main function of the rehabilitation mechanical device is to assist patients in the rehabilitation training of finger flexion and extension. The purpose is to reduce the functional atrophy of the motor nervous system in the patient's brain through training and treatment for a certain period of time, so as to realize the repair of the patient's motor nerves and restore the body. motor function. In actual operation, in order to achieve the effect of training and recovery, the rehabilitation mechanical device needs to help the patient complete multiple specific rehabilitation tr...

AI Technical Summary

Problems solved by technology

[0003] At present, the limitation of applying the traditional iterative learning control method is that it cannot guarantee high displacement control accuracy at all times, and the control effect is greatly affected by external disturbances.

If there is sudden interference during the rehabilitation training process, the rehabilitation effect cannot be guaranteed, and in severe cases, it will cause discomfort to the patient

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