Command Filter Backstepping Sliding Model Control for Lower-Limb Exoskeleton

A command filter adaptive fuzzy backstepping control strategy is proposed for lower-limb assisting exoskeleton. Firstly, the human-robot model is established by taking the human body as a passive part, and a coupling torque is introduced to describe the interaction between the exoskeleton and human leg. Then, Vicon motion capture system is employed to obtain the reference trajectory. For the purpose of obviating the “explosion of complexity” in conventional backstepping, a second-order command filter is introduced into the sliding mode control strategy. The fuzzy logic systems (FLSs) are also applied to handle with the chattering problem by estimating the uncertainties and disturbances. Furthermore, the stability of the closed-loop system is proved based on the Lyapunov theory. Finally, simulation results are presented to illustrate the effectiveness of the control strategy.

[1]  Qun Zong,et al.  ISPS-modular command-filtered adaptive back-stepping control of non-linearly parameterized pure-feedback systems , 2016 .

[2]  Sung Hoon Kim,et al.  Control scheme and networked control architecture for the Berkeley lower extremity exoskeleton (BLEEX) , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[3]  S. Delp,et al.  Musculoskeletal modelling deconstructs the paradoxical effects of elastic ankle exoskeletons on plantar-flexor mechanics and energetics during hopping , 2014, Journal of Experimental Biology.

[4]  Saber Mefoued,et al.  A second order sliding mode control and a neural network to drive a knee joint actuated orthosis , 2015, Neurocomputing.

[5]  Eduardo Piña-Martínez,et al.  Inverse Modeling of Human Knee Joint Based on Geometry and Vision Systems for Exoskeleton Applications , 2015 .

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

[7]  Ángel Gil-Agudo,et al.  Hybrid FES-robot cooperative control of ambulatory gait rehabilitation exoskeleton , 2014, Journal of NeuroEngineering and Rehabilitation.

[8]  Hong Wang,et al.  Leader–follower fixed-time consensus of multi-agent systems with high-order integrator dynamics , 2017, Int. J. Control.

[9]  Qing Guo,et al.  A Lower Extremity Exoskeleton: Human-Machine Coupled Modeling, Robust Control Design, Simulation, and Overload-Carrying Experiment , 2015 .

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

[11]  Rong Song,et al.  Movement Performance of Human–Robot Cooperation Control Based on EMG-Driven Hill-Type and Proportional Models for an Ankle Power-Assist Exoskeleton Robot , 2017, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[12]  Yuanqing Xia,et al.  Sliding mode attitude tracking of rigid spacecraft with disturbances , 2012, J. Frankl. Inst..

[13]  Umashankar Nagarajan,et al.  Integral admittance shaping: A unified framework for active exoskeleton control , 2016, Robotics Auton. Syst..

[14]  Jesus Ortiz,et al.  Robo-Mate an exoskeleton for industrial use : concept and mechanical design , 2016 .

[15]  Wei Dong,et al.  Robust Sliding Mode Control Based on GA Optimization and CMAC Compensation for Lower Limb Exoskeleton , 2016, Applied bionics and biomechanics.

[16]  Li-Xin Wang,et al.  Adaptive fuzzy systems and control , 1994 .

[17]  Hao-Bo Kang,et al.  Adaptive control of 5 DOF upper-limb exoskeleton robot with improved safety. , 2013, ISA transactions.

[18]  Guangdeng Zong,et al.  Command Filter-Based Adaptive Neural Tracking Controller Design for Uncertain Switched Nonlinear Output-Constrained Systems , 2017, IEEE Transactions on Cybernetics.

[19]  Dezhi Xu,et al.  Adaptive Command-Filtered Backstepping Control for Linear Induction Motor via Projection Algorithm , 2016 .

[20]  Maarouf Saad,et al.  Development and control of a robotic exoskeleton for shoulder, elbow and forearm movement assistance , 2012 .

[21]  Xiaoxiang Hu,et al.  Command filtered adaptive fuzzy backstepping control method of uncertain non-linear systems , 2016 .

[22]  Chang-Soo Han,et al.  Human-robot cooperative control based on pHRI (Physical Human-Robot Interaction) of exoskeleton robot for a human upper extremity , 2012 .

[23]  Robert Bogue,et al.  Robotic exoskeletons: a review of recent progress , 2015, Ind. Robot.

[24]  Jiping He,et al.  Adaptive control of a wearable exoskeleton for upper-extremity neurorehabilitation , 2012 .

[25]  Yanhe Zhu,et al.  Double closed-loop cascade control for lower limb exoskeleton with elastic actuation. , 2015, Technology and health care : official journal of the European Society for Engineering and Medicine.

[26]  Liang Liu,et al.  Robust Adaptive State Constraint Control for Uncertain Switched High-Order Nonlinear Systems , 2017, IEEE Transactions on Industrial Electronics.

[27]  Jian Huang,et al.  Nonlinear disturbance observer based sliding mode control of a human-driven knee joint orthosis , 2016, Robotics Auton. Syst..

[28]  Shahid Hussain,et al.  Robust Nonlinear Control of an Intrinsically Compliant Robotic Gait Training Orthosis , 2013, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[29]  Yskandar Hamam,et al.  Rhythmic Trajectory Design and Control for Rehabilitative Walking in Patients with Lower Limb Disorder , 2016, Int. J. Humanoid Robotics.