Optimal prediction control method of tracking errors of all shafts of redundancy rehabilitation walking training robot

Abstract

The invention provides an optimal prediction control method of tracking errors of all shafts of a redundancy rehabilitation walking training robot. According to the control method, on the basis of characteristics of a redundant robot and a dynamic model, a nonlinear feedback predictive controller is designed and discretization prediction models of all shaft sub systems are established; an objective optimization performance function is established by using trajectory tracking errors of all shafts as variables and constraint conditions of the trajectory tracking errors of all shafts, speed tracking errors, and control increments are constructed to obtain optimal prediction control, thereby realizing optimal performances of trajectory tracking errors of all shafts; and the trajectory tracking error and speed tracking error of the redundancy rehabilitation walking training robot are restricted in a designated range to guarantee safety training of a rehabilitee. With the control method, the trajectory tracking precision is improved and safety of the trainer is guaranteed.

Description

Technical field: [0001] The invention relates to the control field of a wheeled redundant rehabilitation robot, in particular to a control method of a wheeled redundant lower limb rehabilitation robot. Background technique: [0002] With the increase of the elderly population and the frequent occurrence of traffic accidents, the number of patients with lower limb motor dysfunction is increasing year by year. Due to the limited rehabilitation medical resources in our country, it is impossible to solve the problem of lower limb rehabilitation of disabled people in time. Therefore, it is of great significance to develop rehabilitation walking training robots to help people with lower limb disabilities to carry out walking training safely. [0003] Rehabilitation walking training robots usually need to track the movement trajectory specified by the doctor to help the disabled to train. Accurate tracking of the doctor's training trajectory can effectively improve the rehabilitat...

AI Technical Summary

Problems solved by technology

There have been many research results on trajectory tracking control methods for rehabilitation walking training robots, but none of the existing achievements have achieved the optimal performance of trajectory tracking in the three directions of motion of the x-axis, y-axis and rotation axis respectively, and have not simultaneously combined the trajectory tracking error and Velocity tracking error constrained within specified range

Rehabilitation robots are different from industrial robots. If the trajectory tracking error is too large, the rehabilitation robot may collide with surrounding obstacles; if the speed tracking error is too large, it will cause the rehabilitation robot and the rehabilitation person to move uncoordinated, which will threaten the safety of the trainer

So far, there is no control method that achieves the optimal trajectory tracking performance of each axis and constrains the trajectory tracking error and speed tracking error at the same time.

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