文献类型：期刊文献

英文题名：Adaptive fuzzy control using ant colony optimization for unknown systems with time-delay

作者：Yinong, Zhang[1]; Hongxing, Li[1]; Yushan, Li[2]

第一作者：张益农

机构：[1] College of Automation, Beijing Union University, Beijing, China; [2] College of Information, Beijing Union University, Beijing, China

第一机构：北京联合大学城市轨道交通与物流学院

年份：2014

卷号：175

期号：7

起止页码：313-320

外文期刊名：Sensors and Transducers

收录：EI(收录号：20151100630357);Scopus(收录号：2-s2.0-84924413330)

语种：英文

外文关键词：Algorithms - Ant colony optimization - Artificial intelligence - Delay control systems - Fuzzy control - Parameter estimation - Real time systems - Time delay - Time varying systems

摘要：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 timedelay. 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.? ? 2014 IFSA Publishing, S. L.