scholarly journals Characteristics and Control Response of the TOPAZ II Reactor System Real-Time Dynamic Simulator

1994 ◽  
Author(s):  
Kwan S. Kwok ◽  
Mohamed S. El-Genk ◽  
Mark D. Hoover
Keyword(s):  
Real Time ◽  
Reactor System ◽  
Time Dynamic ◽  
Control Response ◽  
Dynamic Simulator ◽  
And Control

The structure of a real time dynamic simulator for training (siden)

1987 ◽  
Vol 8 (1) ◽  
pp. 49-63 ◽  
Author(s):  
B. Drozdowicz ◽  
R. Quirós ◽  
A. Schiliuk ◽  
R. Cerro
Keyword(s):  
Real Time ◽  
Time Dynamic ◽  
Dynamic Simulator

NEURAL NETWORK BASED DYNAMIC CONTROLLERS FOR INDUSTRIAL ROBOTS

1995 ◽  
Vol 06 (03) ◽  
pp. 257-271
Author(s):  
SE-YOUNG OH ◽  
WEON-CHANG SHIN ◽  
HYO-GYU KIM
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Network Architecture ◽  
Industrial Robot ◽  
Industrial Robots ◽  
System Stability ◽  
Robot Dynamics ◽  
Time Dynamic ◽  
Dynamic Controller ◽  
And Control

The industrial robot’s dynamic performance is frequently measured by positioning accuracy at high speeds and a good dynamic controller is essential that can accurately compute robot dynamics at a servo rate high enough to ensure system stability. A real-time dynamic controller for an industrial robot is developed here using neural networks. First, an efficient time-selectable hidden layer architecture has been developed based on system dynamics localized in time, which lends itself to real-time learning and control along with enhanced mapping accuracy. Second, the neural network architecture has also been specially tuned to accommodate servo dynamics. This not only facilitates the system design through reduced sensing requirements for the controller but also enhances the control performance over the control architecture neglecting servo dynamics. Experimental results demonstrate the controller’s excellent learning and control performances compared with a conventional controller and thus has good potential for practical use in industrial robots.

Remarks on the software for a real time dynamic simulator (SIDEN)

1987 ◽  
Vol 8 (4) ◽  
pp. 325-337 ◽  
Author(s):  
B. Drozdowicz ◽  
R. Quirós ◽  
A. Schiliuk ◽  
R. Cerro
Keyword(s):  
Real Time ◽  
Time Dynamic ◽  
Dynamic Simulator

UNDERACTUATED HAND DYNAMIC MODELING, ITS REAL-TIME SIMULATION, AND CONTROL

2010 ◽  
Vol 07 (04) ◽  
pp. 609-634 ◽  
Author(s):  
HAI HUANG ◽  
YONG-JIE PANG ◽  
JIANG LI ◽  
SHAO-WEI FAN ◽  
XIN-QING WANG ◽  
...  
Keyword(s):  
Real Time ◽  
Dynamic Model ◽  
Dynamic Models ◽  
Impedance Control ◽  
Differential Algebraic Equations ◽  
Algebraic Equations ◽  
Inverse Dynamic ◽  
Time Dynamic ◽  
Simulation And Control ◽  
And Control

The forward and inverse dynamic models of the underactuated 2-DOF finger have been established in this article based on virtual spring approach. This approach not only avoids the solution of differential-algebraic equations but also leads to a completely decoupled dynamic model that is ideal for directly inverse dynamic analysis, real-time dynamic simulation and control. To verify this approach, an underactuated 3-joint finger has been brought forward. Simulation results from Matlab/Simulink are consistent with those obtained from ADAMS grasp simulations. For the hand real-time dynamic control, the velocity observer has been established based on the dynamic model, the adaptive curve fitting with the observer has obtained precise velocity signals, made up the uncertain parameters such as torsion spring, inertial, damps, etc. and achieved ideal results. By applying dynamics model and observer, the force-based impedance control can realize more accurate and stable force control during grasp.

Sign in / Sign up

Export Citation Format

Share Document