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Chapter 6 Model Order Reduction of Single Input Single Output Systems Using Artificial Bee Colony Optimization Algorithm

机译:第6章使用人工蜂群优化算法的单输入单输出系统模型降阶

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摘要

In many practical situations a fairly complex and high order model is obtained in modeling different components/subsystems of a system. The analysis of such high order system is not only tedious but also cost ineffective for online implementation. Therefore, deriving reduced order models of high-order linear time invariant systems attracted researchers to develop new methods for this purpose. Artificial Bee Colony (ABC) optimization algorithm is an effective and recent addition to swarm based optimization algorithm for optimization in continuous search space. In this paper, Artificial Bee Colony optimization algorithm is applied to solve Model Order Reduction of Single Input Single Output (SISO) Systems. The results obtained by ABC are compared with two most popular deterministic approaches namely Pade and Routh approximation method. The results reported are encouraging and shows that this technique is comparable in quality with existing conventional methods.
机译:在许多实际情况下,在对系统的不同组件/子系统进行建模时会获得相当复杂且高阶的模型。这种高阶系统的分析不仅繁琐,而且在线执行成本低。因此,推导高阶线性时不变系统的降阶模型吸引了研究人员为此目的开发新方法。人工蜂群(ABC)优化算法是基于群体的优化算法的一种有效且最新的方法,用于在连续搜索空间中进行优化。本文采用人工蜂群优化算法求解单输入单输出(SISO)系统的模型降阶问题。将ABC获得的结果与两种最流行的确定性方法(Pade和Routh逼近方法)进行比较。报告的结果令人鼓舞,表明该技术在质量上可与现有常规方法媲美。

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