Gait trajectory planning and fixed-time fuzzy adaptive control for human-exoskeleton cooperative motion based on dynamic movement primitives

A three-loop control strategy is developed for exoskeleton to reduce interaction torque and improve compliance control performance in human-exoskeleton collaborative movement. In the outer loop, dynamic movement primitives is employed to learn one demonstration trajectories of individual walking gaits and to generate the reference trajectory, which serves as the input for the admittance middle layer. In the middle layer, the admittance scheme is designed to determine the desired joint trajectory, which is then input to the inner position control loop of the exoskeleton. Due to model uncertainties in the position control loop, an adaptive fuzzy fixed-time controller is incorporated to approximate uncertain dynamics, and ensures that the exoskeleton’s state errors converge into a small neighborhood around zero within a finite period, regardless of original conditions. This three-loop control strategy has two key advantages: (1) the exoskeleton can identify individual gaits with varying physical features such as motion frequency and amplitude; (2) the operator wearable comfort is significantly improved based on human-exoskeleton impedance and synchronous motion indicators. Finally, both comparative simulations and experimental validations confirm the efficacy of the proposed control framework in achieving smooth and coordinated human-exoskeleton interactions.