Abstract
In order to synchronize human and machine positions and minimize human-machine interaction forces in exoskeleton control, we present a two-degree-of-freedom (2-DOF) upper-limb exoskeleton model with power enhancement and direct force control strategy based on fuzzy adaptive algorithm. The conventional PD controller is widely used in exoskeleton control because it is model independent and its gains can be easily tuned. However, the speed of movement of the operator and the mass of external load are uncertain in practice; hence, the parameters of a conventional PD controller have to be adjusted according to the velocity of the motion and external loads to ensure the effectiveness of trajectory tracking. Additionally, there is a lag in the response time when the operator starts to move or changes direction suddenly. Therefore, this study proposes the use of an adaptive controller combining the fuzzy set techniques and PD controller to improve trajectory tracking. Robustness testing of the fuzzy PD controller for the external load uncertainty and motion velocity change are also investigated. The simulation results clearly indicate the superior performance of the fuzzy adaptive PD controller over the conventional one for tracking performance with external load uncertainty and motion velocity variance.
Highlights
Wearable robots have been developed to assist individuals in a variety of military, medical, and industrial applications [1]
The gains of a PD controller can be automatically adjusted according to the deviation of torque, which plays an important role in making the fuzzy adaptive controller work on a changeable mode
The direct force control strategy consists of two closed-loop controllers, including a PD controller and a PI controller, to synchronize the human-machine positions and to minimize the human-machine interaction forces
Summary
Wearable robots have been developed to assist individuals in a variety of military, medical, and industrial applications [1]. In order to improve trajectory tracking performance, many control strategies for upper-limb exoskeletons have been proposed. Kiguchi and Hayashi [3] proposed an electromyogram-based impedance control method for an upper-limb power-assist exoskeleton robot, incorporating the user’s motion intention. DIRECT FORCE CONTROL OF UPPER-LIMB EXOSKELETON BASED ON FUZZY ADAPTIVE ALGORITHM. Kazerooni [11] developed a direct force feedback to control an upper extremity power assist robot to augment the power of the operator. To further improve the tracking performance, we have designed a direct force control strategy using a fuzzy PD controller for application in power-enhanced upper-limb exoskeleton with varying external loads or different velocities, which contain significant uncertainties.
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