Real-time, dynamic controller for dynamic power filters in supplies with high contamination

1990 ◽  
Author(s):  
G.L. Van Harmelen ◽  
J.H.R. Enslin
Keyword(s):  
Real Time ◽  
Dynamic Power ◽  
Time Dynamic ◽  
Dynamic Controller ◽  
Power Filters

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.

scholarly journals The Backseat Control Architecture for Autonomous Robotic Vehicles: A Case Study with the Iver2 AUV

2010 ◽  
Vol 44 (4) ◽  
pp. 42-54 ◽  
Author(s):  
Donald P. Eickstedt ◽  
Scott R. Sideleau
Keyword(s):  
Real Time ◽  
Autonomous Underwater Vehicle ◽  
Dynamic Control ◽  
Underwater Vehicle ◽  
Control Architecture ◽  
Classical Dynamic ◽  
Time Dynamic ◽  
Intelligent Controller ◽  
Dynamic Controller ◽  
Robotic Vehicles

Abstract In this paper, an innovative hybrid control architecture for real-time control of autonomous robotic vehicles is described as well as its implementation on a commercially available autonomous underwater vehicle (AUV). This architecture has two major components, a behavior-based intelligent autonomous controller and an interface to a classical dynamic controller that is responsible for real-time dynamic control of the vehicle given the decisions of the intelligent controller over the decision state space (e.g., vehicle course, speed, and depth). The driving force behind the development of this architecture was a desire to make autonomy software development for underwater vehicles independent from the dynamic control specifics of any given vehicle. The resulting software portability allows significant code reuse and frees autonomy software developers from being tied to a particular vehicle manufacturer’s autonomy software and support as long as the vehicle supports the required interface between the intelligent controller and the dynamic controller. This paper will describe in detail the components of the backseat driver architecture as implemented on the Iver2 underwater vehicle, provide several examples of its use, and discuss the future direction of the architecture.

Control Model Constructing on Real-Time Dynamic Reversible Lane in Condition of Connected Vehicle

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Lina Mao ◽  
Wenquan Li ◽  
Pengsen Hu ◽  
Guiliang Zhou ◽  
Huiting Zhang ◽  
...  
Keyword(s):  
Real Time ◽  
Control Model ◽  
Connected Vehicle ◽  
Time Dynamic
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