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Vol. 175, Issue 7, July 2014, pp. 313-320

 

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Adaptive Fuzzy Control Using Ant Colony Optimization for Unknown Systems with Time-Delay
 

1 Zhang Yinong, 1 Li Hongxing and 2 Li Yushan

1 College of Automation, Beijing Union University, Beijing, 100101, China
2 College of Information, Beijing Union University, Beijing, 100101, China
1 Tel.: +86 10 64900515, fax: +86 10 64900503

1 E-mail: zdhtyinong@buu.edu.cn, zdhthongxing@buu.com.cn

 

Received: 3 April 2014 /Accepted: 30 June 2014 /Published: 30 July 2014

Digital Sensors and Sensor Sysstems

 

Abstract: An adaptive control method is proposed for the unknown system with time-delay in this paper. There are two main parts. First, in order to effectively control unknown systems with time- delay, Adaline network is used to on-line estimate the unknown steady-state gain and time-delay of the systems and estimated values modify parameters of Smith predictor in real-time. Next, a new method of adaptive fuzzy control using improved ant colony optimization (ACO) algorithm is proposed for controlling the unknown systems with time-delay. The ant colony algorithm is used to optimize the rules and the parameters of the fuzzy controller. This method can also apply to control slow time-varying systems with time-delay. Simulation results show that the method is efficient and practical.

 

Keywords: Smith predictor, parameters estimation, ant colony optimization, fuzzy control, Adaline network.

 

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