Development of efficient identification scheme for nonlinear dynamic systems using swarm intelligence techniques
Development of efficient identification scheme for nonlinear dynamic systems using swarm intelligence techniques
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DOI：
10.1016/j.eswa.2009.05.036
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
B. Majhi;G. Panda
中科院分区：
文献类型：
--
作者：
B. Majhi;G. Panda
本文概述了两种简单而强大的群体智能工具的基本概念和原理：粒子群优化（PSO）和细菌觅食优化（BFO）。将未知对象的自适应辨识问题转化为一个优化问题，并采用粒子群算法和BFO算法进行求解。利用这种新方法对复杂非线性动态对象进行了有效的辨识。
This paper outlines the basic concept and principles of two simple and powerful swarm intelligence tools: the particle swarm optimization (PSO) and the Bacterial Foraging Optimization (BFO). The adaptive identification of an unknown plant has been formulated as an optimization problem and then solved using the PSO and BFO techniques. Using this new approach efficient identification of complex nonlinear dynamic plants have been carried out through simulation study.