Design and Test of Admittance Control with Inner Adaptive Robust Position Control for a Lower Limb Rehabilitation Robot

Although admittance control has been used in rehabilitation robots in many studies as it can realize compliant human-robot interaction, the inner proportional-integral-derivative (PID) controller of conventional admittance schemes is simple and not robust enough. This study presents an admittance control scheme with inner adaptive robust position control (ARC) for a hip-knee-ankle rehabilitation robot. The ARC is capable of eliminating uncertainties and external disturbances. A healthy male subject was required to perform three experiments, including passive exercise (PE) using a position controller, patient-cooperative exercise using an admittance controller (ACE) with fixed and different parameters. The PE experiment results show that the average normalized root mean square deviation (NRMSD) of trajectory tracking of each joint using the ARC is nearly 60% less than that using the PID controller. And the ACE experiment results show that the average NRMSD using the ARC is roughly 45% less than that using the PID controller while the interaction torque using the two controllers are comparable. It demonstrates that the robot becomes not only compliant but also robust based on the proposed control scheme. Moreover, the last experiment results indicate that admittance control with smaller admittance parameters allows the robot to be more compliant.

[1]  Debraj Mukherjee,et al.  Epidemiology and the global burden of stroke. , 2011, World neurosurgery.

[2]  Hao-Bo Kang,et al.  Adaptive robust control of 5 DOF Upper-limb exoskeleton robot , 2015 .

[3]  H. van der Kooij,et al.  Design and Evaluation of the LOPES Exoskeleton Robot for Interactive Gait Rehabilitation , 2007, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[4]  Seul Jung,et al.  Neural network impedance force control of robot manipulator , 1998, IEEE Trans. Ind. Electron..

[5]  Jie Li,et al.  Robust Adaptive Control for a Class of Uncertain Nonlinear Systems with Time-Varying Delay , 2013, TheScientificWorldJournal.

[6]  Mergen H. Ghayesh,et al.  Impedance Control of an Intrinsically Compliant Parallel Ankle Rehabilitation Robot , 2016, IEEE Transactions on Industrial Electronics.

[7]  Qingsong Ai,et al.  Hierarchical Compliance Control of a Soft Ankle Rehabilitation Robot Actuated by Pneumatic Muscles , 2017, Front. Neurorobot..

[8]  Alireza Akbarzadeh,et al.  sEMG-based impedance control for lower-limb rehabilitation robot , 2018, Intell. Serv. Robotics.

[9]  Jian S. Dai,et al.  Control Strategies for Patient-Assisted Training Using the Ankle Rehabilitation Robot (ARBOT) , 2013, IEEE/ASME Transactions on Mechatronics.

[10]  Chin-Su Kim,et al.  Robust visual servo control of robot manipulators with uncertain dynamics and camera parameters , 2010 .

[11]  Mustafa Sinasi Ayas,et al.  Fuzzy logic based adaptive admittance control of a redundantly actuated ankle rehabilitation robot , 2017 .

[12]  R. Riener,et al.  Patient-cooperative strategies for robot-aided treadmill training: first experimental results , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[13]  Liviu Librescu,et al.  Sliding mode robust control of supersonic three degrees-of-freedom airfoils , 2010 .

[14]  Libin Zhang,et al.  Enhanced Robust Motion Tracking Control for 6 Degree-of-freedom Industrial Assembly Robot with Disturbance Adaption , 2018 .

[15]  Wei Meng,et al.  Adaptive Patient-Cooperative Control of a Compliant Ankle Rehabilitation Robot (CARR) With Enhanced Training Safety , 2018, IEEE Transactions on Industrial Electronics.

[16]  Erhan Akdoğan,et al.  The design and control of a therapeutic exercise robot for lower limb rehabilitation: Physiotherabot , 2011 .

[17]  John J. Craig,et al.  Introduction to Robotics Mechanics and Control , 1986 .

[18]  Fatih Ozkul,et al.  Design of an admittance control with inner robust position control for a robot-assisted rehabilitation system RehabRoby , 2011, 2011 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM).

[19]  M. Dam,et al.  The Effects of Long‐term Rehabilitation Therapy on Poststroke Hemiplegic Patients , 1993, Stroke.

[20]  Richard W. Bohannon,et al.  Treatment Interventions for the Paretic Upper Limb of Stroke Survivors: A Critical Review , 2003, Neurorehabilitation and neural repair.

[21]  Xingda Qu,et al.  Hardware Development and Locomotion Control Strategy for an Over-Ground Gait Trainer: NaTUre-Gaits , 2014, IEEE Journal of Translational Engineering in Health and Medicine.

[22]  Rong Song,et al.  The design and control of a 3DOF lower limb rehabilitation robot , 2016 .

[23]  Farzin Piltan,et al.  Design Robust Fuzzy Sliding Mode Control Technique for Robot Manipulator Systems with Modeling Uncertainties , 2013 .

[24]  Hong Cheng,et al.  Evaluation of a Fuzzy-Based Impedance Control Strategy on a Powered Lower Exoskeleton , 2016, Int. J. Soc. Robotics.