Rehabilitation is an area of robotics in which human–robot collaboration occurs, requiring adaptation and compliance. Pneumatic artificial muscles (PAM) are soft actuators that have built-in compliance making them usable for rehabilitation robots. Conversely, arises from nonlinear characteristics generates obstructions modeling controlling actions. It a critical issue limiting the use PAM. In t...

given by (6) can successfully shorten the settling time of h e tracking control at different operation speeds. In our experimental setup the settling time is in the range of 0.50 N 0.65 s for the conveyor belt running between 9.43 N 26.60 c d s . As we have seen, this is a great improvement in the tracking control compared with that where no special care is taken to compensate for the feedback ...

Locomotion is a major component of human activity, and there have been many attempts to reveal its principles through the application of physics and dynamics. Both computer graphics and robotics continue such efforts, but many problems remain unsolved, even in characterizing the simplest case: linear, forward,

Experiments were performed to reveal some of the computational properties of the human motor memory system. We show that as humans practice reaching movements while interacting with a novel mechanical environment, they learn an internal model of the inverse dynamics of that environment. Subjects show recall of this model at testing sessions 24 hours after the initial practice. The representatio...

The robot manipulator joint actuator dynamics and the payload variation are major factors that severely affect the overall dynamics and hence the tracking performance of the direct drives manipulator. This paper proposes a robust and computationally simple approach aimed at compensating the tracking error due to model uncertainty, actuator dynamics, and payload variation for the inverse dynamic...

In this study, a novel control algorithm, based on a P300-based brain-computer interface (BCI) is fully developed to control a 2-DoF robotic arm. Eight subjects including 5 men and 3 women perform a 2-dimensional target tracking in a simulated environment. Their EEG (Electroencephalography) signals from visual cortex are recorded and P300 components are extracted and evaluated to perform a real...

A common technique in neurocontrol is that of controlling a plant by static state feedback using the plant's inverse dynamics, which is approximated through a learning process. It is well known that in this control mode even small approximation errors or, which is the same, small perturbations of the plant may lead to instability. Here, a novel approach is proposed to overcome the problem of in...

Controlling a high degree of freedom humanoid robot arm to be dextrous and compliant in its movements is a critical task in robot control. The dynamics of such flexible and light manipulators have a highly non-linear nature, making analytical closed form solutions using rigid body assumptions inappropriate. In this thesis, we use Locally Weighted Projection Regression to learn online the invers...

The purpose of this study is to apply inverse dynamics control for a six degree of freedom flight simulator motion system. Imperfect compensation of the inverse dynamic control is intentionally introduced in order to simplify the implementation of this approach. The control strategy is applied in the outer loop of the inverse dynamic control to counteract the effects of imperfect compensation. ...