Abstract

A critical issue in the model-based control of performance-augmenting exoskeleton systems is the unknown nonlinear dynamic properties of the systems or the uncertainties. An improper estimation of the system dynamics can cause instabilities in the system and generate considerable human-exoskeleton interaction forces during human motions. Thus, the controller of such exoskeleton systems needs to add robustness to stabilize it against the uncertainties. In this paper, we propose a global fast sliding mode control algorithm integrated in a hybrid controller for each exoskeleton leg to minimize human-exoskeleton interaction forces. By doing so, the proposed algorithm does not require an exact estimation of the dynamic properties of the exoskeleton system, but still minimizes the physical human-exoskeleton interaction (pHEI) forces. Finally, the performance of the proposed algorithm is verified by experiments on our lower exoskeleton system, which is used for human power augmentation and called “PRMI” exoskeleton. Our experimental results show that the proposed control algorithm provides a good control quality for the PRMI exoskeleton. The PRMI exoskeleton can support a wearer carrying heavy load while tracking the rapid movements of the wearer without obstructing them.

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