Ultra-local model-based prescribed performance assist-as-needed control for series elastic actuator-based upper limb patient-exoskeleton system under complex state constraints

In this paper, an ultra-local model-based prescribed performance assist-as-needed control scheme (UPPAC) is presented for series elastic actuator-based upper limb patient-exoskeleton system (SULPES) subject to complex state constraints. The complex state constraints are introduced to adjust constraint on assistive torque change rate according to the assistive torque error, so as to avoid the rapid change of the assistive torque caused by overshoot and ensure the safety of the patient. In the outer impedance sub-control loop, the desired assistive torque is calculated by an impedance controller. Then, to reduce dependence on precise model parameters, the inner torque sub-control loop is proposed based on the ultra-local model and neural approximation. Combine integral barrier Lyapunov function with backstepping strategy, the prescribed constraints for tracking error and complex state constraints are satisfied. Finally, both theoretical proof and co-simulation illustrate the effectiveness of the proposed UPPAC.