Nonlinear Disturbance Observer-Based Control Design for a Robotic Exoskeleton Incorporating Fuzzy Approximation

Abstract

To perform power augmentation tasks of a robotic exoskeleton, this paper utilizes fuzzy approximation and designed disturbance observers for compensating the disturbance torques caused by unknown input saturation, fuzzy approximation errors, viscous friction, gravity and payloads. The proposed adaptive fuzzy control with updated parameters mechanism and additional torque inputs by using the disturbance observers are exerted into the robotic exoskeleton via feed-forward loops to counteract to the disturbances. Through such an approach, the system does not need any requirement of built-in torque sensing units. In order to validate the proposed framework, the extensive experiments are conducted on the upper limb exoskeleton using the state feedback and output feedback control to illustrate the performance the proposed approaches.

Advances in Disturbance/Uncertainty Estimation and Attenuation [Guest editors' introduction]

“…In reference [1], authored by Li et al, the problem of robotic exoskeleton control is considered based on disturbance estimation technique with the aim to removing built-in torque sensing units. To this end, fuzzy approximation and disturbance observers are utilized to estimate and compensate the disturbance torques caused by viscous friction, gravity, payloads and unknown input saturation.…”

Neural control for constrained human-robot interaction with human motion intention estimation and impedance learning

“…Neural networks (NNs) are usually employed to handle uncertainties in the models [15], [16]. In [17], an adaptive fuzzy control design and a nonlinear disturbance observer are proposed in the design of a human upper limb exoskeleton. NNs can be not only applied to handle uncertainties in robot models, but also solve the problem about the human motion intention estimation and impedance parameters learning as mentioned above.…”

Filtered Backstepping Control Based on the Nonlinear Disturbance Observer for Nonlinear System

“…To solve the control problem for nonlinear system with unknown disturbances, the fuzzy neural network based sliding mode control method is proposed in [1][2], the fuzzy neural network is used to estimate the unknown disturbances. In [3], the sliding mode control is used to solve the uncertainties.…”