Upper Limb Exoskeleton Rehabilitation Robot Control System Research

The upper extremity exoskeleton repetitive therapy robot is one kind of medical device which uses in hemiparalysis patient being restored to health. This thesis mainly discuss the control system of this robot equipment, thus causes the therapy robot to be possible to adopt the corresponding control policy according to patient’s actual situation, thus achieves the accurate control the goal. Uniting the traditional impedance control method and iteration learning control algorithm, therefore proposed one kind of learning impedance control algorithm, this method makes up two closed loops structures, the algorithm simple. The position data and the strength data as the initial datum and the online cyclical examination obtain, the generalized return neural network to be the target input parameter carries on the kinematics the fast adjust. This thesis discusses static characteristic of PAM driver, and give the basic application framework to the robot control system. In this article, it take MRDS as the robot develop platform, designed medical recovery service pattern, in views of user experience, has completed the control software modular, so that the operators could use, has given one kind of robot control concrete software and the hardware realizes the form. The paper has carried on the computer simulation research work in fundamental research’s foundation, and has carried out the massive experimental study in the recovery robot control experiment platform, and further proposed the research direction and the duty.