Application Research On Motion Control For Exoskeleton Upper Limb Rehabilitation Robot

With the research of the upper limb rehabilitation robot assisting hemiplegia patients to carry out rehabilitation training to deepen,the existing problems in the interaction movement control of the robot are gradually revealed.The exoskeleton upper limb rehabilitation robot has complicated structure,a lot of uncertainty will come into being in contact with patients.In the process of interactive training,there are also problems such as motion intention detection,upper limb movement correction,assisted force adjustment and the acquisition of reference motion trajectory.In order to improve the effectiveness of rehabilitation training,the control method should always pay attention to mobilize the patient's own initiative feedback on motion effects.In this dissertation,the application research on motion control for exoskeleton upper limb rehabilitation robot was studied in the aspects of robot model establishment,motion control,interaction strategy,reference trajectory and assisted interaction combined with virtual reality.The main research work is summarized as follows:(1)Systematic analysis of exoskeleton upper limb rehabilitation robot.The whole upper limb rehabilitation robot is divided into six irregular rods connected by rotating joints,according to the mechanical structure of the exoskeleton upper limb rehabilitation robot,and the physical simulation model of the robot is established in the Simulink environment.The transfer relationship of speed between the links and the Jacobian matrix are given according to the kinematics equation of the robot.The dynamic equation of the exoskeleton upper limb rehabilitation robot is deduced according to the Lagrangian modeling method.The simulation results have verified the accuracy of the modeling method.It also shows that the exoskeleton upper limb rehabilitation robot is a complex multivariable and strongly coupled affine nonlinear system.(2)Data-driven model-free adaptive sliding mode control of exoskeleton robot.Aiming at the problem that the motion control model of rehabilitation robot is complex and there is uncertain disturbance in the process of motion,an approximate discrete dynamic linearization method of robot dynamics model is proposed in this dissertation.The robot model is estimated online by using the input and output data of the system,which solves the problem that the controlled object model is complex and difficult to establish accurately.The data-driven model-free adaptive sliding mode control law is designed to realize the accurate tracking control of articular motion of multi-joint exoskeleton upper limb rehabilitation robot in uncertain interference environment.The design method of the controller is simple and does not depend on the analytical model of the robot,which makes it has strong robustness.Extensive simulations also demonstrate the effectiveness and robustness of the control method.(3)Trajectory acquisition and passive motion tracking control for upperlimb rehabilitation robot.In order to ensure that the motion trajectory of the rehabilitation robot is in accordance with the law of upper limb movement,the robot kinematics method is used to convert the human healthy upper limbs' activities of daily life into robot trajectory.The kinematic model of the upper limb of the human body and the robot is solved together,the transformation function which transforms the upper limb joint node trajectory information into the motion trajectory of the robot is got.A fuzzy logic controller is designed and used in the passive trajectory tracking control,to achieve the rehabilitation training that the hemiplegia upper limb is forced driven by the healthy upper limb.The validity of the reference trajectory acquisition and passive tracking control scheme is verified by simulation and experiment.(4)Active interaction motion control for upper limb rehabilitation robot with constraint of reference trajectory.The active motion intention of each joint is obtained according to the human-robot interaction torque information.A kind of model-free adaptive filter is given to deal with the problem of the motion intention judgment caused by the interruption and mutation of the torque signal.In order to ensure that the patient can complete the specified action and prevent the emergence of sports compensation in the active rehabilitation training,an active interaction motion control method for upper limb rehabilitation robot with constraint of reference trajectory is given.Based on the impedance control,this method adds the trajectory constraint and compensation force term to implement the upper limb motion attitude correction and auxiliary force adjustment during active interaction motion.Through the parameter setting,the active interaction motion controller can realize the conversion of three training modes such as active,resisting and assisting,and can also be applied in trajectory tracking control of passive training.A large number of simulations have verified the effectiveness of the control method.(5)Development of virtual reality assisted interactive training system.Combining virtual reality technology with the motion control of exoskeleton upper limb rehabilitation robot,a virtual reality assisted interactive training system based on motion intention is developed.That realizes the intuitive feedback of the information during the process of rehabilitation training and achieves the "human in loop" control effect.With the virtual environment providing visual feedback and interactive state information,the active interactive motion controller adjusting the robot to assist the patient's upper limb along the reference trajectory for rehabilitation training,this system can provide on-line guidance for the size and orientation of active motion intentions in the process of upper limb rehabilitation training,and to achieve the effect of patient involvement in training motivation and multi-sensory stimulation.The training results of the simulation and experimental tests have shown that the developed system can realize the re-learning of the subjects with the reference action.