Abstract

Wearable lower limb hydraulic exoskeletons can be used to augment the human performance in heavy load transportation. Nonlinear and walking phase-dependent dynamics make the lower limb hydraulic exoskeleton become difficult to be modeled. This paper presents a generalized multiphase dynamic modeling method in which the dynamic model of each walking phase can all be solved based on a general higher dimensional dynamic model and different holonomic constraints. Compared to traditional lower limb exoskeleton modeling methods where the modeling of each walking phase is done independently, the proposed method is simple and applicable to arbitrary walking phases, especially for double leg support phase (closed-chain dynamics). Based on the established dynamic models, MIMO adaptive robust cascade force controllers (ARCFC) are designed both for double leg support phase and single leg support phase to effectively address high-order nonlinearities and various modeling uncertainties in hydraulic exoskeletons. An additional torque allocation method is proposed to deal with the overactuated characteristic in double leg support. Comparative simulations are conducted to verify the excellent human-machine interaction force control performance of the proposed scheme.

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