The Experts below are selected from a list of 1221 Experts worldwide ranked by ideXlab platform

Ziguang Yin - One of the best experts on this subject based on the ideXlab platform.

  • Zhang Dynamics based Tracking Control of Knee Exoskeleton with Timedependent Inertial and Viscous Parameters
    International Journal of Control Automation and Systems, 2018
    Co-Authors: Ziguang Yin
    Abstract:

    Knee exoskeleton plays an important role in robot-assisted rehabilitation for impaired pilots to restore their motor functionality of lower extremity through producing external movement compensation. Tracking control of knee exoskeleton often encounters time-dependent (time-varying) issues reflected in its dynamic behaviors. In many applications, inertial and viscous parameters of knee exoskeletons are measured to be time-dependent due to unexpected mechanical vibrations and contact interactions, which increases difficultly of accurate control of knee exoskeleton to follow Desired Joint Angle trajectories. This paper proposes a novel control strategy for controlling knee exoskeleton with time-dependent (time-varying) inertial and viscous coefficients. Such controller is designed based on Zhang dynamics (ZD) method and utilizes twice Zhang function (ZF) so as to make the tracking error of Joint Angle exponentially converge to zero. Illustrative simulation examples and experimental validation are presented to show efficiency of this type of controller based on ZD method. Comparisons with gradient dynamic (GD) approach are also presented to demonstrate superiority of ZD-type control strategy for tracking Joint Angle of knee exoskeleton.

  • Tracking control of time-varying knee exoskeleton disturbed by interaction torque.
    ISA transactions, 2017
    Co-Authors: Ziguang Yin, Hongliang Guo
    Abstract:

    Knee exoskeletons have been increasingly applied as assistive devices to help lower-extremity impaired people to make their knee Joints move through providing external movement compensation. Tracking control of knee exoskeletons guided by human intentions often encounters time-varying (time-dependent) issues and the disturbance interaction torque, which may dramatically put an influence up on their dynamic behaviors. Inertial and viscous parameters of knee exoskeletons can be estimated to be time-varying due to unexpected mechanical vibrations and contact interactions. Moreover, the interaction torque produced from knee Joint of wearers has an evident disturbance effect on regular motions of knee exoskeleton. All of these points can increase difficultly of accurate control of knee exoskeletons to follow Desired Joint Angle trajectories. This paper proposes a novel control strategy for controlling knee exoskeleton with time-varying inertial and viscous coefficients disturbed by interaction torque. Such designed controller is able to make the tracking error of Joint Angle of knee exoskeletons exponentially converge to zero. Meanwhile, the proposed approach is robust to guarantee the tracking error bounded when the interaction torque exists. Illustrative simulation and experiment results are presented to show efficiency of the proposed controller. Additionally, comparisons with gradient dynamic (GD) approach and other methods are also presented to demonstrate efficiency and superiority of the proposed control strategy for tracking Joint Angle of knee exoskeleton.

  • Tracking control of knee exoskeleton system with time-dependent inertial and viscous parameters
    IFAC-PapersOnLine, 2017
    Co-Authors: Ziguang Yin, Hong Cheng
    Abstract:

    Abstract Knee exoskeleton plays an important role in robot-assisted rehabilitation for impaired pilots to restore their motor functionality of lower extremity through producing external movement compensation. Tracking control of knee exoskeleton often encounters time-dependent (time-varying) issues reflected in its dynamic behaviors. In many applications, inertial and viscous parameters of knee exoskeletons are measured to be time-dependent due to unexpected mechanical vibrations and contact interactions, which increases difficultly of accurate control of knee exoskeleton to follow Desired Joint Angle trajectories. This paper proposes a novel control strategy for controlling knee exoskeleton with time-dependent (time-varying) inertial and viscous coefficients. Such controller is designed based on Zhang dynamics (ZD) method so as to make the tracking error of Joint Angle exponentially converge to zero. Illustrative examples are presented to show efficiency of this type of controller based on ZD method. Comparisons with gradient dynamic (GD) approach are also presented to demonstrate superiority of ZD-type control strategy for tracking Joint Angle of knee exoskeleton.

  • Tracking control of knee exoskeleton with time-varying model coefficients under compliant interaction
    2017 36th Chinese Control Conference (CCC), 2017
    Co-Authors: Ziguang Yin
    Abstract:

    Knee exoskeletons can help injured subjects regain locomotion ability by providing external movement compensation as a robot-assisted rehabilitation technique. Tracking control of Joint Angle of knee exoskeletons often encounters time-dependent (time-varying) model parameter issues, which would dramatically put an influence up on dynamic behaviors. In a number of applications, inertial and viscous parameters of knee exoskeletons are estimated to be time-dependent (time-varying) due to unexpected mechanical vibrations and contact interactions. Moreover, to achieve adaptively compliant interaction torque between the human and the robot will contribute to have an positive effect on comfortable experience on wearers. However, All of these may increase difficultly of accurate control of knee exoskeleton to follow Desired Joint Angle trajectories. This paper proposes a novel control strategy for controlling knee exoskeleton with time-dependent (time-varying) inertial and viscous coefficients, with disturbance interaction torque from pilots considered as well. Such controller is designed based on Zhang dynamics (ZD) method and utilizes twice Zhang function (ZF) so as to make the tracking error of Joint Angle of knee exoskeletons exponentially converge to zero. Meanwhile, such ZD based method is robust to guarantee the tracking error bounded when the gap between the disturbance torque and the exoskeleton torque always exists. Illustrative examples are presented to show efficiency of this type of controller based on ZD method. Comparisons with gradient dynamic (GD) approach are also presented to demonstrate efficiency and superiority of ZD-type control strategy for tracking Joint Angle of knee exoskeleton.

Suguru Arimoto - One of the best experts on this subject based on the ideXlab platform.

  • ICRA - Iterative learning scheme for a redundant manipulator: Skilled hand writing motion on an arbitrary smooth surface
    2011 IEEE International Conference on Robotics and Automation, 2011
    Co-Authors: Kenji Tahara, Suguru Arimoto
    Abstract:

    This paper proposes an iterative learning control scheme for a redundant manipulator to acquire a skilled hand writing motion of its end-point specified on an arbitrary smooth surface. Firstly, the existence of a unique solution to the Lagrange equation of motion of the robot, whose end-point motion is coincident with a given Desired end-point trajectory described in Cartesian coordinate system, is shown theoretically. Second, the iterative learning control signal that enables the robot end-point to trace a Desired trajectory specified on an arbitrary smooth surface with fulfilling a Desired contact force is designed. Next, a numerical simulation for the iterative learning scheme is conducted to show the effectiveness of the proposed controller, and its result is compared to a theoretically derived Desired Joint Angle trajectory. This comparison shows that there exists a unique solution of the Desired Joint Angle trajectory when an initial pose of the manipulator and a Desired end-point trajectory on the constraint surface are given, even under the existence of holonomic constraint and Joint redundancy.

  • Feedback control for robotic manipulator with an uncertain Jacobian matrix
    Journal of Robotic Systems, 1999
    Co-Authors: Chien Chern Cheah, Sadao Kawamura, Suguru Arimoto
    Abstract:

    In most applications of robots, a Desired path for the end-effector is usually specified in task space such as Cartesian space. One way to move the robot along this path is to solve the inverse kinematics problem to generate the Desired Angles in Joint space. However, it is a very time consuming task to solve the inverse kinematics problem. Furthermore, in the presence of uncertainty in kinematics, it is impossible to derive the Desired Joint Angle from the Desired end-effector path and the Jacobian matrix of the mapping from Joint space to task space. In this article, a feedback control law using an uncertain Jacobian matrix is proposed for setpoint control of robots. Sufficient conditions for the bound of the estimated Jacobian matrix and stability conditions for the feedback gains are presented to guarantee the stability and passivity of the robots. A gravity regressor with an uncertain Jacobian matrix is also proposed for gravitational force compensation when the gravitational force is uncertain. Simulation results are presented to illustrate the performance of the proposed controllers. ©1999 John Wiley & Sons, Inc.

  • Asymptotic stability of robot control with approximate Jacobian matrix and its application to visual servoing
    Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187), 1
    Co-Authors: Chien Chern Cheah, K. Lee, Sadao Kawamura, Suguru Arimoto
    Abstract:

    In order to describe a task for the robot manipulator, a Desired path for the end effector is usually specified in task space such as Cartesian space. In the presence of uncertainty in kinematics, it is impossible to derive the Desired Joint Angle from the Desired end effector path by solving the inverse kinematics problem. In addition, the Jacobian matrix of the mapping from Joint space to task space could not be exactly derived. We present feedback control laws for setpoint control of a robot with uncertain kinematics and Jacobian matrix from Joint space to task space. Sufficient conditions for the bound of the estimated Jacobian matrix and stability conditions for the feedback gains are presented to guarantee the stability of the robot's motion. Simulation results are presented to illustrate the performance of the proposed controllers.

Rolf Eckmiller - One of the best experts on this subject based on the ideXlab platform.

  • ICRA - Learning friction estimation for sensorless force/position control in industrial manipulators
    Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C), 1
    Co-Authors: V. Zahn, R. Maass, M. Dapper, Rolf Eckmiller
    Abstract:

    We present a novel type of friction estimation applied to the field of sensorless force/position control. As part of a position based neural force control (NFC-P) the estimation friction and external force allows a force/position control without using a force sensor. NFC-P consists of a hybrid force/position controller that accurately generates contact forces to objects with arbitrary flexibility and uncertain distance or shape. NFC-P performs force control by modifying the Desired Joint Angle changes in force direction before they are fed into a computed torque controller. The inverse dynamics of the manipulator is modeled in a computed torque controller. Kinematic mappings guarantee singularity robustness in the entire workspace. Results from real time experiments are presented with a 6-DOF industrial manipulator as a testbed.

  • ICRA - Hard contact surface tracking for industrial manipulators with (SR) position based force control
    Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C), 1
    Co-Authors: R. Maas, V. Zahn, M. Dapper, Rolf Eckmiller
    Abstract:

    We present a novel control concept that solves a wide range of surface tracking tasks for manipulators with defined contact to (moving) rigid objects. The position based neural force control (NFC-P) consists of a hybrid force/position controller that accurately generates contact forces to objects with arbitrary flexibility and uncertain distance or shape. NFC-P performs force control by modifying the Desired Joint Angle changes in force direction. These are fed into a computed torque controller, where the inverse dynamics of the manipulator is represented by neural networks. NFC-P includes a neural trajectory generating tool for smooth and kinematical valid contact trajectories with the possibility to adapt the trajectories to the unknown shape of the surface online. The kinematical mappings guarantee singularity robustness (SR) in the entire workspace. Results from real-time experiments are presented using a 6-DOF industrial manipulator as testbed.

Hongliang Guo - One of the best experts on this subject based on the ideXlab platform.

  • Tracking control of time-varying knee exoskeleton disturbed by interaction torque.
    ISA transactions, 2017
    Co-Authors: Ziguang Yin, Hongliang Guo
    Abstract:

    Knee exoskeletons have been increasingly applied as assistive devices to help lower-extremity impaired people to make their knee Joints move through providing external movement compensation. Tracking control of knee exoskeletons guided by human intentions often encounters time-varying (time-dependent) issues and the disturbance interaction torque, which may dramatically put an influence up on their dynamic behaviors. Inertial and viscous parameters of knee exoskeletons can be estimated to be time-varying due to unexpected mechanical vibrations and contact interactions. Moreover, the interaction torque produced from knee Joint of wearers has an evident disturbance effect on regular motions of knee exoskeleton. All of these points can increase difficultly of accurate control of knee exoskeletons to follow Desired Joint Angle trajectories. This paper proposes a novel control strategy for controlling knee exoskeleton with time-varying inertial and viscous coefficients disturbed by interaction torque. Such designed controller is able to make the tracking error of Joint Angle of knee exoskeletons exponentially converge to zero. Meanwhile, the proposed approach is robust to guarantee the tracking error bounded when the interaction torque exists. Illustrative simulation and experiment results are presented to show efficiency of the proposed controller. Additionally, comparisons with gradient dynamic (GD) approach and other methods are also presented to demonstrate efficiency and superiority of the proposed control strategy for tracking Joint Angle of knee exoskeleton.

Xue Jia-wei - One of the best experts on this subject based on the ideXlab platform.

  • Adaptive robust predictive control for robotic manipulator based on uncertain parameter approximation
    Control theory & applications, 2012
    Co-Authors: Xue Jia-wei
    Abstract:

    A multi-input-multi-output adaptive robust predictive control method is presented to solve the trajectory tracking problem of robotic manipulator system with uncertain parameters and unknown external disturbances.A nonlinear robust predictive controller is first designed for the robotic manipulator system,and then a supervisory control is added to the controller.The function approximation is employed to approximate the unknown terms in the predictive control law caused by uncertain system model and external disturbances.It is proved that the proposed controller can make robotic manipulator track the Desired Joint Angle trajectory without static error.Simulation results show the effectiveness of the method.