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
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;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
DOI :
10.1109/WCICA.2010.5554886