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首页> 外文期刊>Journal of control science and engineering >System Identification of Heat-Transfer Process of Frequency Induction Furnace for Melting Copper Based on Particle Swarm Algorithm
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System Identification of Heat-Transfer Process of Frequency Induction Furnace for Melting Copper Based on Particle Swarm Algorithm

机译:基于粒子群算法的变频感应熔铜炉传热过程系统辨识

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摘要

An adaptive evolutionary strategy in standard particle swarm optimization is introduced. Adaptive evolution particle swarm optimization is constructed to improve the capacity of global search. A method based on adaptive evolution particle swarm optimization for identification of continuous system with time delay is proposed. The basic idea is that the identification of continuous system with time delay is converted to an optimization of continuous nonlinear function. The adaptive evolution particle swarm optimization is utilized to find an optimal solution of continuous nonlinear function. Convergence conditions are given by the convergence analysis based on discrete time linear dynamic system theory. Numerical simulation results show that the proposed method is effective for a general continuous system with time delay and the system of heat-transfer process of frequency induction furnace for melting copper.
机译:介绍了标准粒子群算法中的自适应进化策略。构建自适应进化粒子群优化算法以提高全局搜索的能力。提出了一种基于自适应进化粒子群算法的时滞连续系统辨识方法。基本思想是将具有时滞的连续系统的识别转换为连续非线性函数的优化。利用自适应进化粒子群算法找到连续非线性函数的最优解。通过基于离散时间线性动力系统理论的收敛性分析,给出了收敛条件。数值模拟结果表明,该方法对于一般的带时延的连续系统以及频率感应炉的铜熔炼传热系统是有效的。

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