Task-space Feedback Control for A Two-link Arm Driven by Six Muscles with Variable Damping and Elastic Properties

2006 ◽  
Author(s):  
K. Tahara ◽  
Zhi-Wei Luo ◽  
S. Arimoto ◽  
H. Kino
Keyword(s):  
Feedback Control ◽  
Elastic Properties ◽  
Task Space ◽  
Variable Damping

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.

A Synergy-Based Motor Control Framework for the Fast Feedback Control of Musculoskeletal Systems

2019 ◽  
Vol 141 (3) ◽  
Author(s):  
Reza Sharif Razavian ◽  
Borna Ghannadi ◽  
John McPhee
Keyword(s):  
Motor Control ◽  
Feedback Control ◽  
Real Time ◽  
Three Dimensional ◽  
Muscle Synergies ◽  
Task Space ◽  
Computationally Efficient ◽  
Control Framework ◽  
Muscle Activations ◽  
Musculoskeletal Systems

This paper presents a computational framework for the fast feedback control of musculoskeletal systems using muscle synergies. The proposed motor control framework has a hierarchical structure. A feedback controller at the higher level of hierarchy handles the trajectory planning and error compensation in the task space. This high-level task space controller only deals with the task-related kinematic variables, and thus is computationally efficient. The output of the task space controller is a force vector in the task space, which is fed to the low-level controller to be translated into muscle activity commands. Muscle synergies are employed to make this force-to-activation (F2A) mapping computationally efficient. The explicit relationship between the muscle synergies and task space forces allows for the fast estimation of muscle activations that result in the reference force. The synergy-enabled F2A mapping replaces a computationally heavy nonlinear optimization process by a vector decomposition problem that is solvable in real time. The estimation performance of the F2A mapping is evaluated by comparing the F2A-estimated muscle activities against the measured electromyography (EMG) data. The results show that the F2A algorithm can estimate the muscle activations using only the task-related kinematics/dynamics information with ∼70% accuracy. An example predictive simulation is also presented, and the results show that this feedback motor control framework can control arbitrary movements of a three-dimensional (3D) musculoskeletal arm model quickly and near optimally. It is two orders-of-magnitude faster than the optimal controller, with only 12% increase in muscle activities compared to the optimal. The developed motor control model can be used for real-time near-optimal predictive control of musculoskeletal system dynamics.

H/sub ∞/ tuning for task-space feedback control of robot with uncertain Jacobian matrix

2001 ◽  
Vol 46 (8) ◽  
pp. 1313-1318 ◽  
Author(s):  
C.C. Cheah ◽  
S. Kawamura ◽  
S. Arimoto ◽  
K. Lee
Keyword(s):  
Feedback Control ◽  
Jacobian Matrix ◽  
Task Space

Postural Balance of an Underactuated Biped Robot With a Reaction Wheel

2017 ◽  
Author(s):  
Chris M. Maurice ◽  
Bill Goodwine ◽  
James P. Schmiedeler
Keyword(s):  
Feedback Control ◽  
Postural Balance ◽  
Biped Robot ◽  
Zero Dynamics ◽  
Total System ◽  
Task Space ◽  
Reaction Wheel ◽  
Control Laws ◽  
Biped Robots ◽  
Nonlinear Control Theory

Practical and effective biped robots are trending toward reality with increasing interest in the technology and recent major innovations in nonlinear control theory. The development of underactuated techniques transitioned biped robot walking to a more elegant human-like motion. When disturbances are encountered, maintaining postural balance becomes a proven challenge that limits the practicality of these machines. This paper offers a solution to this issue by showing that an underactuated five-link reaction wheel-equipped planar biped robot can be posturally balanced successfully and efficiently with feedback control laws derived from the system’s zero dynamics and through task space optimization. The zero dynamics controller is shown to exhibit better performance compared to the task space controller in terms of settling time and total system work.

Smart Fluid Damping: Shaping the Force/Velocity Response through Feedback Control

2000 ◽  
Vol 11 (12) ◽  
pp. 945-958 ◽  
Author(s):  
Neil D. Sims ◽  
Roger Stanway ◽  
Andrew R. Johnson ◽  
David J. Peel ◽  
William A. Bullough
Keyword(s):  
Feedback Control ◽  
Linear Feedback ◽  
Order Function ◽  
Bingham Plastic ◽  
Smart Fluids ◽  
Fluid Damping ◽  
Variable Damping ◽  
Velocity Characteristic ◽  
Force Velocity ◽  
Feedback Control Strategy

It is now well known that smart fluids [electrorheological (ER) and magnetorheological (MR)] can form the basis of controllable vibration damping devices. With both types of fluid, however, the force/velocity characteristic of the resulting damper is significantly non-linear, possessing the general form associated with a Bingham plastic. In a previous paper the authors showed that by using a linear feedback control strategy it is possible to produce the equivalent of a viscous damper with a continuously variable damping coefficient. In the present paper the authors illustrate an extension of the technique, by showing how the shape of the force/velocity characteristic can be controlled through feedback control. This is achieved by using a polynomial function to generate a set point based upon the damper velocity. The response is investigated for polynomial functions of zero, 1st and 2nd order. It is shown how the damper can accurately track higher order polynomial shaping functions, while the zero-order function is particularly useful in illustrating the dynamics of the closed-loop system.

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