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Vol. 160, Issue 12, December 2013, pp. 578-583

 

Bullet

 

Neural Network Control of Large Time-Delay Object Based on Chaos Ant Colony Optimization
 
Wei-Dong WANG

Engineering Center, Nanjing Institute of Railway Technology, Nanjing, 210031, China
E-mail: njwangwwd@163.com

 

Received: 16 October 2013   /Accepted: 22 November 2013   /Published: 30 December 2013

Digital Sensors and Sensor Sysstems

 

Abstract: In order to study the way of controlling the large delay object, this paper introduces the chaos ant colony algorithm to the neural network control of large time-delay. It is found that chaos ant colony algorithm is an algorithm that steady astatic, good dynamic performance, and it has certain robustness, but it is also easy to appear stagnation phenomenon in the evolution process. This study constructs an intelligent neural network as a controller through improving the fuzzy PID control. Under this control scheme, improve ant colony algorithm through introducing chaos searching mechanism, and then use it in the off-line optimization of controller's parameters. The experimental results show that the scheme and its optimization strategy can effectively improve the performance of the system.

 

Keywords: Chaos ant colony optimization, TSP, PID, Large time-delay.

 

 

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