External sensory feedback control for end-effector of flexible multi-link manipulators

2002 ◽  
Author(s):  
H.G. Lee ◽  
S. Kawamura ◽  
F. Miyazaki ◽  
S. Arimoto
Keyword(s):  
Feedback Control ◽  
Sensory Feedback ◽  
End Effector

Task-Space Control Design and Performance Evaluation for a 6DOF Stewart Nanoscale Platform

2008 ◽  
Author(s):  
Chun-Chung Li ◽  
Yung Ting ◽  
Yi-Hung Liu ◽  
Yi-Da Lee ◽  
Chun-Wei Chiu
Keyword(s):  
Feedback Control ◽  
Hybrid Control ◽  
Feedforward Control ◽  
Feedback Controller ◽  
Test Method ◽  
Computation Method ◽  
Task Space ◽  
Force Output ◽  
End Effector ◽  
Control Scheme

A 6DOF Stewart platform using piezoelectric actuators for nanoscale positioning objective is designed. A measurement method that can directly measure the pose (position and orientation) of the end-effector is developed so that task-space on-line control is practicable. The design of a sensor holder for sensor employment, a cuboid with referenced measure points, and the computation method for obtaining the end-effector parameters is introduced. A control scheme combining feedforward and feedback is proposed. The inverse model of a hysteresis model derived by using a dynamic Preisach method is used for the feedforward control. Hybrid control to maintain both the positioning and force output for nano-cutting and nano-assembly applications is designed for the feedback controller. The optimal gain of the feedback controller is searched by using relay feedback test method and genetic algorithm. In experiment, conditions with/without external load employed with feedforward, feedback, and feedforward with feedback control schemes respectively are carried out. Performance of each control scheme verifies the capability of achieving nanoscale precision. The combined feedforward and feedback control scheme is superior to the others for gaining better precision.

scholarly journals Cerebellar patients have intact feedback control that can be leveraged to improve reaching

2019 ◽  
Author(s):  
Amanda M. Zimmet ◽  
Amy J. Bastian ◽  
Noah J. Cowan
Keyword(s):  
Feedback Control ◽  
Healthy Subjects ◽  
Sensory Feedback ◽  
Control Process ◽  
Movement Control ◽  
The Body ◽  
Smith Predictor ◽  
Feedback Gain ◽  
Phase Lag ◽  
Predictive Role

ABSTRACTIt is thought that the brain does not simply react to sensory feedback, but rather uses an internal model of the body to predict the consequences of motor commands before sensory feedback arrives. Time-delayed sensory feedback can then be used to correct for the unexpected—perturbations, motor noise, or a moving target. The cerebellum has been implicated in this predictive control process. Here we show that the feedback gain in patients with cerebellar ataxia matches that of healthy subjects, but that patients exhibit substantially more phase lag. This difference is captured by a computational model incorporating a Smith predictor in healthy subjects that is missing in patients, supporting the predictive role of the cerebellum in feedback control. Lastly, we improve cerebellar patients’ movement control by altering (phase advancing) the visual feedback they receive from their own self movement in a simplified virtual reality setup.

scholarly journals Cerebellar patients have intact feedback control that can be leveraged to improve reaching

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Amanda M Zimmet ◽  
Di Cao ◽  
Amy J Bastian ◽  
Noah J Cowan
Keyword(s):  
Feedback Control ◽  
Healthy Subjects ◽  
Sensory Feedback ◽  
Control Process ◽  
Movement Control ◽  
The Body ◽  
Smith Predictor ◽  
Feedback Gain ◽  
Phase Lag ◽  
Predictive Role

It is thought that the brain does not simply react to sensory feedback, but rather uses an internal model of the body to predict the consequences of motor commands before sensory feedback arrives. Time-delayed sensory feedback can then be used to correct for the unexpected—perturbations, motor noise, or a moving target. The cerebellum has been implicated in this predictive control process. Here, we show that the feedback gain in patients with cerebellar ataxia matches that of healthy subjects, but that patients exhibit substantially more phase lag. This difference is captured by a computational model incorporating a Smith predictor in healthy subjects that is missing in patients, supporting the predictive role of the cerebellum in feedback control. Lastly, we improve cerebellar patients’ movement control by altering (phase advancing) the visual feedback they receive from their own self movement in a simplified virtual reality setup.

Combining Motion Primitives and Image-Based Visual Servo Control

2020 ◽  
Author(s):  
Ghananeel Rotithor ◽  
Ashwin P. Dani
Keyword(s):  
Feedback Control ◽  
Open Loop ◽  
Servo Control ◽  
Visual Servo ◽  
Motion Generation ◽  
End Effector ◽  
Visual Servo Control ◽  
Dynamic Movement ◽  
Motion Primitive ◽  
Dynamic Movement Primitives

Abstract Combining perception feedback control with learning-based open-loop motion generation for the robot’s end-effector control is an attractive solution for many robotic manufacturing tasks. For instance, while performing a peg-in-the-hole or an insertion task when the hole or the recipient part is not visible in the eye-in-the-hand camera, an open-loop learning-based motion primitive method can be used to generate end-effector path. Once the recipient part is in the field of view (FOV), visual servo control can be used to control the motion of the robot. Inspired by such applications, this paper presents a control scheme that switches between Dynamic Movement Primitives (DMPs) and Image-based Visual Servo (IBVS) control combining end-effector control with perception-based feedback control. A simulation result is performed that switches the controller between DMP and IBVS to verify the performance of the proposed control methodology.

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