Analysis and comparison of optimization algorithm for network flow control

2003 ◽  
Author(s):  
Hao Zhang ◽  
Zhong-Ping Jiang ◽  
Yi Fan ◽  
S. Panwar
Keyword(s):  
Flow Control ◽  
Optimization Algorithm ◽  
Network Flow

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.

scholarly journals A Cooperative Intermodal Transportation Network Flow Control Method Based on Model Predictive Control

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Yuankai Huang ◽  
Qicai Zhou ◽  
Xiaolei Xiong ◽  
Jiong Zhao
Keyword(s):  
Model Predictive Control ◽  
Flow Control ◽  
Real Time ◽  
Predictive Control ◽  
Dynamic Optimization ◽  
Network Flow ◽  
Control Method ◽  
Discrete Event ◽  
Transport Systems ◽  
Intermodal Transport

With the development of information technology, intermodal transport research pays more attention to dynamic optimization and multi-role cooperation. The core issue of this paper was to realize container routing with dynamic adjustment, real-time optimization, and multi-role cooperation characteristics in the intermodal transport network. This paper first introduces the Intermodal Transport Cooperation Protocol (ITCP) that describes the operation and analysis of intermodal transport systems with the concept of encapsulation and layering. Then, a new network flow control method was built based on Model Predictive Control (MPC) in the ITCP framework. The method takes real-time information from all ITCP layers as input and generates flow control decisions for containers. To evaluate the method’s effectiveness, a discrete event simulation experiment is applied. The results show that the proposed method outperforms the all-or-nothing method in scenarios with high freight volume, which means the method proposed in this paper can effectively balance the network transport load and reduce network operating costs. The research of this paper may throw some new light on intermodal transport research from the perspectives of digitization, multi-role cooperation, dynamic optimization, and system standardization.

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