DocumentCode
1699138
Title
An analytical design of improved PID Neural Network controller for AQM
Author
Hou, Ping ; Wang, Zhiquan
Author_Institution
Sch. of Autom., Nanjing Univ. of Sci. & Technol., Nanjing, China
fYear
2010
Firstpage
4907
Lastpage
4910
Abstract
Internet congestion control system is complex, uncertainty and nonlinear. An Improved PID Neural Network (I-PID-NN) controller with changing integration rate and incomplete derivation in hidden layer is applied in active queue management (AQM). The adjustment of neural network parameters are implemented by using gradient algorithm as learning the rules, and the probability of packet loss can achieve adaptation. The performance of the I-PID-NN controller is verified by NS2 simulation results, which shows higher robustness and link utilization than PID-NN.
Keywords
Internet; control system synthesis; gradient methods; learning systems; neurocontrollers; nonlinear control systems; queueing theory; stability; telecommunication congestion control; three-term control; uncertain systems; AQM; Internet congestion control system; NS2 simulation; PID neural network controller; active queue management; analytical design; changing integration rate; control uncertainty; gradient algorithm; incomplete derivation; link utilization; nonlinear control; packet loss probability; robustness; rule learning; Algorithm design and analysis; Artificial neural networks; Control systems; Convergence; Robustness; Simulation; Stability analysis; PID Neural Network; active queue management (AQM); network congestion control;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location
Jinan
Print_ISBN
978-1-4244-6712-9
Type
conf
DOI
10.1109/WCICA.2010.5554886
Filename
5554886
Link To Document