Research On Control Strategy For Omnidirectional Rehabilitative Training Walker With Tracking Errors Constraints

With the consolidation of the aging of population and the increase of patients with walking dysfunction,rehabilitation doctors cannot complete the heavy walking training task,which has led to a great development of the rehabilitation walking training robot.Rehabilitative training walkers usually need to track the training trajectories prescribed by doctors to assist patients in walking rehabilitation exercise.Due to the impact of load changes,the controller gain parameter perturbation,human-robot interaction force and other uncertain factors,the rehabilitation robot could hardly track the specified path accurately,and tracking errors often exceed the expected constraints.So far,a lot of achievements have been made on the tracking control of walking rehabilitation training robot,but these achievements did not take into account the position tracking error and velocity tracking error simultaneous constraints while realizing the trajectory tracking or velocity tracking.Restricting tracking errors within specified range can not only improve the tracking accuracy but also ensure the safety of the patient.For this purpose,in this paper,the error constraint tracking control problem is studied based on predictive control theory,and the main idea is as follows:By the method of approximate linearization and discretization,the predictive model of the discrete form of the rehabilitative robot was established on the basis of the dynamic model of the omnidirectional rehabilitative training walker.Based on this prediction model,the safety prediction controller and auxiliary motion trajectory were designed,the constraint conditions of tracking errors were established,such that the trajectory tracking and velocity tracking were simultaneously completed and the tracking errors were restricted within specified range for any initial values.The simulation and experiment results demonstrate that the proposed safety predictive control algorithm meets position and velocity tracking errors simultaneous constraints for any initial position state.For the presence of additive gain perturbations in the implemented controller,a non-fragile predictive controller was designed and the error prediction model was obtained,which was based on position and velocity tracking error constraints.The first-error-state constraint conditions were established on the basis of the previous error constraint conditions.Stability analysis verifies that the tracking error system is exponentially stable under designed safety prediction controller.The simulation studies prove that the proposed non-fragile safety prediction controller has sufficient non-fragility while constraining tracking errors.The interaction force between patients and rehabilitative robots was separated from the input control force of the dynamic model above that would be considered as a disturbance from the input channel within the system.The extended state model considering interaction force was established,and an extended state observer was designed to estimate the interaction force.The stability of the extended state observer was proved by constructing the Lyapunov function based on the extend model above.A nonlinear controller was designed based on the estimation of an extended state observer,and combined with the prediction control theory,the trajectory and velocity tracking errors with interaction disturbance were simultaneously constrained.Simulation results demonstrate the effectiveness of the extended state observer and the nonlinear controller.