The application of Multivariable Regulator Approach to sewer network flow control

2008 ◽  
Author(s):  
Lv Jianchao ◽  
Fan Liping ◽  
Yang Lin
Keyword(s):  
Flow Control ◽  
Network Flow ◽  
Sewer Network

Multivariable Regulator Approach to Sewer Network Flow Control

1999 ◽  
Vol 125 (3) ◽  
pp. 267-276 ◽  
Author(s):  
Magdalene Marinaki ◽  
Markos Papageorgiou ◽  
Albert Messmer
Keyword(s):  
Flow Control ◽  
Network Flow ◽  
Sewer Network

Novel Network Flow Control Model on Multi-Team Game Theory

2010 ◽  
Vol 32 (2) ◽  
pp. 267-271 ◽  
Author(s):  
Hui-bin Feng ◽  
Shun-yi Zhang ◽  
Chao Liu ◽  
Jue-fu Liu
Keyword(s):  
Game Theory ◽  
Flow Control ◽  
Network Flow ◽  
Control Model ◽  
Team Game

Feasibility Study on the Use of a Voice Coil Motor Direct Drive Flow Rate Control Valve

2009 ◽  
Author(s):  
Shuai Wu ◽  
Richard Burton ◽  
Zongxia Jiao ◽  
Juntao Yu ◽  
Rongjie Kang
Keyword(s):  
Neural Network ◽  
Flow Control ◽  
Flow Rate ◽  
Rate Control ◽  
Network Flow ◽  
Voice Coil Motor ◽  
Direct Drive ◽  
Hydraulic Test ◽  
Servo Valve ◽  
Flow Rate Control

This paper considers the feasibility of a new type of voice coil motor direct drive flow control servo valve. The proposed servo valve controls the flow rate using only a direct measurement of the spool position. A neural network is used to estimate the flow rate based on the spool position, velocity and coil current. The estimated flow rate is fed back to a closed loop controller. The feasibility of the concept is established using simulation techniques only at this point. All results are validated by computer co-simulation using AMESim and Simulink. A simulated model of a VCM-DDV (Voice Coil Motor-Direct Drive Valve) and hydraulic test circuit are built in an AMESim environment. A virtual digital controller is developed in a Simulink environment in which the feedback signals are received from the AMESim model; the controller outputs are sent to the VCM-DDV model in AMESim (by interfacing between these two simulation packages). A LQR (Linear Quadratic Regulator) state feedback and nonlinear compensator controller for spool position tracking is considered as this is the first step for flow control. A flow rate control loop is subsequently included via a neural network flow rate estimator. Simulation results show that this method could control the flow rate to an acceptable degree of precision, but only at low frequencies. This kind of valve can find usage in open loop hydraulic velocity control in many industrial applications.

Efficient implementation of globally-aware network flow control

2012 ◽  
Vol 72 (11) ◽  
pp. 1412-1422 ◽  
Author(s):  
Lizhong Chen ◽  
Ruisheng Wang ◽  
Timothy M. Pinkston
Keyword(s):  
Flow Control ◽  
Network Flow ◽  
Efficient Implementation

scholarly journals Virtual Pheromone Based Network Flow Control For Modular Robotic Systems

Electronics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 481
Author(s):  
Van Tung Le ◽  
Trung Dung Ngo
Keyword(s):  
Flow Control ◽  
Network Flow ◽  
Communication Channel ◽  
Routing Algorithm ◽  
Robotic System ◽  
Robotic Systems ◽  
Application Development ◽  
Gradient Based ◽  
Communication Path

Guaranteeing data transmission between modules is the key for application development of modular robotic systems. In a multi-channel modular robotic system, intersection modules play an essential role of communication channel selection in controlling data flow toward desired destinations. The gradient-based routing algorithm is an ideal solution to create an one-way communication path from any robotic module to a designated destination. To create bi-directional communication for a communication path of robotic configuration, virtual pheromone-based routing algorithm is a promising mechanism for intersection modules due to its simplicity and distributivity. In this paper, we address a virtual pheromone based network flow control based on the integration of gradient and virtual pheromone-based routing algorithms. We validated this method through an education and entertainment application using our newly developed modular robotic system.

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