Research On Coordination Control Strategy Of Lower Limb Exoskeleton Robo

The key to robot-assisted human rehabilitation training with lower limb exoskeletons is to accurately obtain the human-machine motion state based on the implementation of a suitable auxiliary control strategy.At present,most of the research on coordination control strategies of lower limb exoskeleton robots at home and abroad adopts the method of predefined joint trajectory tracking,which sacrifices the wearer’s autonomous movement intention to a certain extent,and the human-machine coordination depends on the matching degree between the predefined joint trajectory and the wearer’s own gait habit,which has the disadvantages of poor adaptability and low reliability.To this end,this paper proposes an adaptive exoskeleton coordination control strategy based on gait phase estimation to achieve a booster assist for wearers with autonomous movement intentions.In this paper,we firstly analyze the human walking motion characteristics in detail,establish the kinematic and Lagrangian dynamics model of the two-linked lower limb exoskeleton,and build an exoskeleton power-assisted simulation system containing PID control method and linear active disturbance rejection control method in MATLAB-Simulink environment.Then,the human motion state information(such as joint posture angle,angular velocity,and plantar pressure)is preprocessed by Butterworth low-pass filter and unitization method,and a gait phase division method based on multi-sensor data fusion is constructed to divide the gait into Initial Swing phase(IW),Full Swing phase(FW),Initial Supported phase(IS)and Fully Supported phase(FS)by fuzzy logic rules.Finally,a hybrid oscillator gait phase estimation control method is designed to replace the adaptive oscillator(AO)for phase estimation during the walking speed switching phase using angle mode phase estimator(AMPE)based on the angle curve,and revert to AO for phase estimation when the walking speed is stable.This solves the problem of slow convergence or even non-convergence of the traditional AO for gait phase estimation during the walking speed switching phase,and the design of the segmented torque generator solves the problem of unstable torque during the transition between the oscillation phase and the support phase.The experimental system of lower limb exoskeleton robot is constructed,and the proposed adaptive exoskeleton coordination control strategy based on gait phase estimation is proved to have lower phase estimation error and better assist force effect compared with the traditional AO-based control strategy and Phase oscillator(PO)-based control strategy through the assist experiments of switching between different walking speeds in treadmill and outdoor walking scenarios.