Abstract
Lower extremity exoskeleton is an intelligent system used in the military and medical rehabilitation field. Its control methods can be divided into model-based control method and model-free control method. In model-based control method, it is required to design the control rates based on the exoskeleton dynamics characteristic to maintain good dynamics. However, the dynamic model of exoskeleton is a complex non-linear system with multi-inputs and multi-outputs. It is difficult to obtain a precise model describing the dynamic characteristics. In addition, a precise exoskeleton dynamics model will increase the computational complexity. In this paper, the dynamic model of the lower extremity exoskeleton is established based on Lagrange method, and the unknown parameters in the dynamic model are identified by the Least-Square Method to obtain a more accurate system dynamics model. Then, the output results are used as the dynamic compensation of the force control inner loop in robot driving joint. The simulation results show the dynamic compensation algorithm can improve the tracking accuracy and dynamic performance of robot control.
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