Robust Adaptive Impedance Control With Application to a Transfemoral Prosthesis and Test Robot

被引:18
|
作者
Azimi, Vahid [1 ]
Fakoorian, Seyed Abolfazl [2 ]
Thang Tien Nguyen [3 ]
Simon, Dan [2 ]
机构
[1] Georgia Inst Technol, Sch Elect & Comp Engn, Atlanta, GA 30332 USA
[2] Cleveland State Univ, Dept Elect Engn & Comp Sci, Cleveland, OH 44115 USA
[3] Ton Duc Thang Univ, Fac Elect & Elect Engn, Modeling Evolutionary Algorithms Simulat & Artifi, Ho Chi Minh City, Vietnam
基金
美国国家科学基金会;
关键词
robust adaptive impedance control; transfemoral prosthesis; nonscalar boundary layer trajectories; VIRTUAL CONSTRAINT CONTROL; WALKING; SYSTEM; VARIABILITY; DESIGN; TIME; LEG;
D O I
10.1115/1.4040463
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents, compares, and tests two robust model reference adaptive impedance controllers for a three degrees-of-freedom (3DOF) powered prosthesis/test robot. We first present a model for a combined system that includes a test robot and a transfemoral prosthetic leg. We design these two controllers, so the error trajectories of the system converge to a boundary layer and the controllers show robustness to ground reaction forces (GRFs) as nonparametric uncertainties and also handle model parameter uncertainties. We prove the stability of the closed-loop systems for both controllers for the prosthesis/test robot in the case of nonscalar boundary layer trajectories using Lyapunov stability theory and Barbalat's lemma. We design the controllers to imitate the biomechanical properties of able-bodied walking and to provide smooth gait. We finally present simulation results to confirm the efficacy of the controllers for both nominal and off-nominal system model parameters. We achieve good tracking of joint displacements and velocities, and reasonable control and GRF magnitudes for both controllers. We also compare performance of the controllers in terms of tracking, control effort, and parameter estimation for both nominal and off-nominal model parameters.
引用
收藏
页数:15
相关论文
共 50 条
  • [1] Switched Robust Tracking/Impedance Control for an Active Transfemoral Prosthesis
    Warner, Holly
    Simon, Dan
    Mohammadi, Hadis
    Richter, Hanz
    2016 AMERICAN CONTROL CONFERENCE (ACC), 2016, : 2187 - 2192
  • [2] Robust Tracking Control of a Prosthesis Test Robot
    Richter, Hanz
    Simon, Dan
    JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME, 2014, 136 (03):
  • [3] Quadratic Programming and Impedance Control for Transfemoral Prosthesis
    Zhao, Huihua
    Kolathaya, Shishir
    Ames, Aaron D.
    2014 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2014, : 1341 - 1347
  • [4] Model-free robust adaptive integral sliding mode impedance control of knee-ankle-toe active transfemoral prosthesis
    Wu, Zhengen
    Chen, Yawei
    Geng, Yanli
    Wang, Xirui
    Xuan, Bokai
    INTERNATIONAL JOURNAL OF MEDICAL ROBOTICS AND COMPUTER ASSISTED SURGERY, 2022, 18 (03):
  • [5] An adaptive impedance control algorithm; application in exoskeleton robot
    Ataei, M. M.
    Salarieh, H.
    Alasty, A.
    SCIENTIA IRANICA, 2015, 22 (02) : 519 - 529
  • [6] Robust Composite Adaptive Transfemoral Prosthesis Control with Non-Scalar Boundary Layer Trajectories
    Azimi, Vahid
    Simon, Dan
    Richter, Hanz
    Fakoorian, Seyed Abolfazl
    2016 AMERICAN CONTROL CONFERENCE (ACC), 2016, : 3002 - 3007
  • [7] An Adaptive Hybrid Control Architecture for an Active Transfemoral Prosthesis
    Mazumder, Aniket
    Hekman, Edsko E. G.
    Carloni, Raffaella
    IEEE ACCESS, 2022, 10 : 52008 - 52019
  • [8] Application of model reference adaptive control to industrial robot impedance control
    Kamnik, R
    Matko, D
    Bajd, T
    JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 1998, 22 (02) : 153 - 163
  • [9] Application of Model Reference Adaptive Control to Industrial Robot Impedance Control
    Roman Kamnik
    Drago Matko
    Tadej Bajd
    Journal of Intelligent and Robotic Systems, 1998, 22 : 153 - 163
  • [10] Robust Control of a Powered Transfemoral Prosthesis Device with Experimental Verification
    Azimi, Vahid
    Shu, Tony
    Zhao, Huihua
    Ambrose, Eric
    Ames, Aaron D.
    Simon, Dan
    2017 AMERICAN CONTROL CONFERENCE (ACC), 2017, : 517 - 522