Modification to model reference adaptive control of 5-link exoskeleton with gravity compensation

This paper presents a modified methodology based on the model reference adaptive control (MRAC) for tracking and stability with gravity compensation for the 5-link single support phase lower limb exoskeleton with external disturbance. Different from conventional methods, the proposed method is based on MRAC with adaptive error gain in the presence of external disturbance. Asymptotical stability of the system is investigated by choosing an appropriate lyapunov function, that ensures the convergence of tracking error to zero. The effectiveness of proposed method has been verified with the help of simulation example.

[1]  Qiong Wu,et al.  Dynamic modeling and sliding mode control of a five-link biped during the double support phase , 2004, Proceedings of the 2004 American Control Conference.

[2]  Vladimir Dobrokhodov,et al.  Adaptive speed control for autonomous surface vessels , 2013, 2013 OCEANS - San Diego.

[3]  José Luis Gordillo,et al.  Kinematics and Dynamics of a New 16 DOF Humanoid Biped Robot with Active Toe Joint , 2012 .

[4]  T. Madani,et al.  Model reference adaptive control using a neural compensator to drive an active knee joint orthosis , 2015, 2015 IEEE International Conference on Rehabilitation Robotics (ICORR).

[5]  Youngjoon Han,et al.  Adaptive Gait Pattern Generation of Biped Robot based on Human's Gait Pattern Analysis , 2007 .

[6]  Vitor Santos,et al.  Mechatronic Design of a New Humanoid Robot with Hybrid Parallel Actuation , 2012 .

[7]  A. Taherifar,et al.  A fast kinematic-based control method for lower-limb power augmentation exoskeleton , 2014, 2014 Second RSI/ISM International Conference on Robotics and Mechatronics (ICRoM).

[8]  Yin Yang,et al.  5-Link model based gait trajectory adaption control strategies of the gait rehabilitation exoskeleton for post-stroke patients , 2010 .

[9]  S.K. Agrawal,et al.  Active Leg Exoskeleton (ALEX) for Gait Rehabilitation of Motor-Impaired Patients , 2007, 2007 IEEE 10th International Conference on Rehabilitation Robotics.

[10]  Kevin A. Wise,et al.  Robust and Adaptive Control: With Aerospace Applications , 2012 .

[11]  R. Lozano,et al.  Model and control of the ELLTIO with two degrees of freedom , 2013, 2013 17th International Conference on System Theory, Control and Computing (ICSTCC).

[12]  Jong H. Park,et al.  Biped robot walking using gravity-compensated inverted pendulum mode and computed torque control , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[13]  Wen Yu,et al.  A novel linear PID controller for an upper limb exoskeleton , 2010, 49th IEEE Conference on Decision and Control (CDC).

[14]  Narong Aphiratsakun,et al.  Balancing Control of AIT Leg Exoskeleton Using ZMP based FLC , 2009 .

[15]  Kevin A. Wise,et al.  Robust and Adaptive Control , 2013 .

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

[17]  Noureddine Golea,et al.  NEURAL NETWORK-BASED MRAC CONTROL OF DYNAMIC NONLINEAR SYSTEMS , 2006 .

[18]  Nhan T. Nguyen Adaptive Control for Linear Uncertain Systems with Unmodeled Dynamics Revisited via Optimal Control Modification , 2013 .

[19]  Wei Meng,et al.  Recent development of mechanisms and control strategies for robot-assisted lower limb rehabilitation , 2015 .

[20]  Renquan Lu,et al.  Development and Learning Control of a Human Limb With a Rehabilitation Exoskeleton , 2014, IEEE Transactions on Industrial Electronics.

[21]  Amar Goléa,et al.  Nonlinear model reference adaptive control using Takagi-Sugeno fuzzy systems , 2006, J. Intell. Fuzzy Syst..

[22]  Shahid Hussain,et al.  Adaptive Impedance Control of a Robotic Orthosis for Gait Rehabilitation , 2013, IEEE Transactions on Cybernetics.