DocumentCode :
120988
Title :
Patient cooperative adaptive controller for lower limb Robotic Rehabilitation Device
Author :
Anwar, Toni ; Al Jumaily, Adel
Author_Institution :
Sch. of Electr., Mech. & Mechatron. Syst., Univ. of Technol. Sydney, Sydney, NSW, Australia
fYear :
2014
fDate :
21-22 Feb. 2014
Firstpage :
1469
Lastpage :
1474
Abstract :
This is evident that training duration is a key factor for a successful therapy. Robot supported therapy can improve the rehabilitation allowing more intensive training. This paper presents the kinematic, the control architecture and benchmark criteria to evaluate the performance of Robotic Rehabilitation Devices (RRD). Equipped with position, force and impedance controller, the proposed RRD can deliver the patient cooperative lower limb therapy taking into account the patient activity and supporting him/her only as much as needed[1]. One of the main objectives of a successful lower limb robotic rehabilitation device is to obtain a smooth human machine interaction in different phase of gait cycle at the interaction point (haptic behavior). The input (interaction force, Joint angle, rate of change of interaction force) and output (impedance, Δτ) relationship of the control system is nonlinear. This paper proposes a fuzzy rule based controller to be used to control the interaction force at the patient exoskeleton interaction point. In achieving the objective, impedance, driver torque and angular velocity have been modulated in a way such that there is a reduction of interaction force. Minimum interaction force at the interaction point and tracking the defined gait trajectory with minimum error are set as the benchmark to evaluate the performance in many tasks. In this paper there is an evaluation of what degree of impedance is ideal for what type of interaction force and joint angle to maintain a trajectory tunnel. This paper describes the control architecture of one Degree of freedom lower limb exoskeleton that has been specifically designed in order to ensure a proper trajectory control for guiding patient´s limb along an adaptive reference gait pattern [2]. The proposed methodology satisfies all the desired criteria to be an ideal robotic rehabilitation device.
Keywords :
adaptive control; force control; fuzzy control; haptic interfaces; medical robotics; patient treatment; position control; RRD; adaptive reference gait pattern; control architecture; force controller; fuzzy rule; gait trajectory; haptic behavior; impedance controller; interaction force; joint angle; lower limb robotic rehabilitation device; patient cooperative adaptive controller; patient exoskeleton interaction point; position controller; rate of change; robot supported therapy; smooth human machine interaction; trajectory tunnel; Exoskeletons; Force; Impedance; Joints; Robots; Torque; Trajectory; Inertia; PID; admittance; damping; fuzzy logic; impedance; interaction Force; joint; stance; stiffness coefficient; swing phase; trajectory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advance Computing Conference (IACC), 2014 IEEE International
Conference_Location :
Gurgaon
Print_ISBN :
978-1-4799-2571-1
Type :
conf
DOI :
10.1109/IAdCC.2014.6779542
Filename :
6779542
Link To Document :
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