Research On Sliding Mode Tracking Control Of Rehabilitation Walking Training Robot

As the trend of aging continues to deepen,there is an increasing demand for the use of rehabilitation walking training robots to perform neural remodeling for people with lower limb impairments.The rehabilitation walking training robot needs to track the movement trajectory specified by the physician during the training process,however,in the actual operation,the incomplete output information of the system due to factors such as aging sensors results in unsatisfactory tracking accuracy,and even if the desired trajectory can be tracked,the convergence time is excessively sacrificed,putting the patient’s safety at risk.In order to solve the above problems,this thesis takes a rehabilitation walking training robot as the research object,and conducts relevant research on the incomplete feedback information of the control system,mainly including:When the rehabilitation walking training robot helps the patient to carry out rehabilitation training,the influence of the patient quality on the robot’s center of gravity is inevitable.Therefore,this thesis further establishes a dynamic model with incomplete feedback information based on the basic dynamic model of gravity shift,which lays a foundation for the following research.Aiming at the control problem of the rehabilitation walking training robot subject to incomplete feedback information in the process of movement,a sliding mode tracking control method was proposed based on the dynamics model of incomplete feedback information.The state observer and sliding mode tracking controller were designed respectively.According to Lyapunov stability theory,it is proved that the system can achieve asymptotic stability under the action of state observer and sliding mode tracking controller,and the stability of the system can be realized by MATLAB simulation.The incomplete feedback information is regarded as a kind of uncertain disturbance,based on which,the control problem of convergence time is further considered.A trajectory tracking control method that can converge quickly under uncertain disturbance is proposed.A radial basis function neural network is used to approximate and compensate the disturbance term,and a fixed-time sliding mode tracking controller is further designed.The stability of the controller was proved according to Lyapunov stability theory,and the fast convergence of the rehabilitation robot system at a fixed time was verified by MATLAB simulation,and the approximation effect of radial basis neural network was verified by comparison simulation,so that the rehabilitation walking training robot could accurately track the specified training trajectory.