Iterative Estimator-Based Nonlinear Backstepping Control of a Robotic Exoskeleton
A repetitive training movement is an efficient method
to improve the ability and movement performance of stroke survivors
and help them to recover their lost motor function and acquire new
skills. The ETS-MARSE is seven degrees of freedom (DOF)
exoskeleton robot developed to be worn on the lateral side of the
right upper-extremity to assist and rehabilitate the patients with
upper-extremity dysfunction resulting from stroke. Practically,
rehabilitation activities are repetitive tasks, which make the
assistive/robotic systems to suffer from repetitive/periodic
uncertainties and external perturbations induced by the high-order
dynamic model (seven DOF) and interaction with human muscle
which impact on the tracking performance and even on the stability
of the exoskeleton. To ensure the robustness and the stability of the
robot, a new nonlinear backstepping control was implemented with
designed tests performed by healthy subjects. In order to limit and to
reject the periodic/repetitive disturbances, an iterative estimator was
integrated into the control of the system. The estimator does not need
the precise dynamic model of the exoskeleton. Experimental results
confirm the robustness and accuracy of the controller performance to
deal with the external perturbation, and the effectiveness of the
iterative estimator to reject the repetitive/periodic disturbances.
Backstepping control, iterative control,
Modeling and Control of a 4DoF Robotic Assistive Device for Hand Rehabilitation
For those who have lost the ability to move their hand, going through repetitious motions with the assistance of a therapist is the main method of recovery. We have been developed a robotic assistive device to rehabilitate the hand motions in place of the traditional therapy. The developed assistive device (RAD-HR) is comprised of four degrees of freedom enabling basic movements, hand function, and assists in supporting the hand during rehabilitation. We used a nonlinear computed torque control technique to control the RAD-HR. The accuracy of the controller was evaluated in simulations (MATLAB/Simulink environment). To see the robustness of the controller external disturbance as modelling uncertainty (±10% of joint torques) were added in each joints.
Biorobotics, rehabilitation, nonlinear control, robotic assistive device, exoskeleton.
Tracking Trajectory of a Cable-Driven Robot for Lower Limb Rehabilitation
This paper investigates and presents a cable-driven
robot to lower limb rehabilitation use in sagittal plane. The presented
rehabilitation robot is used for a trajectory tracking in joint space.
The paper covers kinematic and dynamic analysis, which reveals
the tensionability of the used cables as being the actuating source
to provide a rehabilitation exercises of the human leg. The desired
trajectory is generated to be used in the control system design in joint
space. The obtained simulation results is showed to be efficient in
this kind of application.
Cable-driven multibody system, computed-torque
controller, lower limb rehabilitation, tracking trajectory.
Lyapunov-Based Tracking Control for Nonholonomic Wheeled Mobile Robot
This paper presents a tracking control strategy based on Lyapunov approach for nonholonomic wheeled mobile robot. This control strategy consists of two levels. First, a kinematic controller is developed to adjust the right and left wheel velocities. Using this velocity control law, the stability of the tracking error is guaranteed using Lyapunov approach. This kinematic controller cannot be generated directly by the motors. To overcome this problem, the second level of the controllers, dynamic control, is designed. This dynamic control law is developed based on Lyapunov theory in order to track the desired trajectories of the mobile robot. The stability of the tracking error is proved using Lupunov and Barbalat approaches. Simulation results on a nonholonomic wheeled mobile robot are given to demonstrate the feasibility and effectiveness of the presented approach.
Mobile robot, trajectory tracking, Lyapunov, stability.