A motion control method for upper limb rehabilitation robot rehabilitation training

Abstract

A motion control method for rehabilitation training of an upper limb rehabilitation robot. The process is: ① Establishing a state equation: The upper limb rehabilitation robot dynamic model based on Lagrangian gives the assumption conditions, converts the upper limb rehabilitation robot system equation into a specific expression form and compensates ; ② State equation transformation, design H ∞ The robust repetitive controller makes the system asymptotically stable; ③ Then the upper limb rehabilitation robot rehabilitation training motion control is carried out. Based on Equation (34), the control requirements satisfy the conditions for the establishment of Theorem 1. Based on the characteristics of the upper limb rehabilitation robot model and based on the upper limb rehabilitation robot training mode, the present invention proposes a state feedback robust repetitive control of the upper limb rehabilitation robot with multi-period input signals; by introducing state feedback, the multi-period repetitive controller design problem is transformed into a state feedback design To improve the tracking performance and robust stability of uncertain systems. The simulation results show that the present invention can achieve high-precision fast tracking and high system stability.

Description

technical field [0001] The invention relates to the overall scheme design and application technical field of the rehabilitation training motion control part of an upper limb rehabilitation robot, and in particular provides a rehabilitation training motion control method of an upper limb rehabilitation robot. Background technique [0002] The basic control structure of the robot is usually divided into two parts: the mechanism body and the control system; the function of the control system is to operate and control the mechanism body according to the user's instructions, and complete various actions of the job. The performance of the controller system largely determines the performance of the robot. The schematic diagram of the basic control structure of the robot is as follows: image 3 shown. [0003] image 3 Among them, X represents the running trajectory of the end of the robot in the desired Cartesian coordinate system; the trajectory generation link obtains the kinema...

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Problems solved by technology

[0006] Although the above-mentioned control methods for uncertain robots have achieved certain results in theory and application, there are still problems such as large amount of calculation, difficulty in guaranteeing real-time performance, parameter drift or prone to "chattering" phenomenon, etc.

The upper limb rehabilitation robot studied in this paper is a special robot that assists or replaces physicians in performing rehabilitation training for affected limbs. When controlling the upper limb rehabilitation machine, it is necessary to consider the particularity of the patient’s wear and the repetition of rehabilitation training. The existing It is uncertain that the control method of the robot cannot fully meet the control requirements of the upper limb rehabilitation machine. Therefore, it is necessary to study its suitable control method according to the characteristics of the upper limb rehabilitation robot

[0007] In the process of rehabilitation training, the purpose of the dynamic control of the upper limb rehabilitation robot is to ensure the accuracy of the trajectory of the upper limb rehabilitation robot and the stability of the system operation. The main influencing factors are: (1) The rehabilitation training of the upper limb rehabilitation robot is a long-term process, when the upper limb rehabilitation robot is required to perform the same task for a long period of time, component wear and aging will have an impact on the repeated positioning accuracy; (2) the training method of the upper limb rehabilitation robot is adjusted in real time according to the patient's training status, in many applications Upper limb rehabilitation robots often need to reprogram new tasks. At this time, temperature changes in the control system and the surrounding environment, as well as transient response conditions between system stop and start, will affect the positioning accuracy; (3) in the upper limb rehabilitation robot model Uncertain factors such as arm active force and time-varying torque will affect the stability of the system

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