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状态转移算法原理与应用

周晓君 阳春华 桂卫华

周晓君, 阳春华, 桂卫华. 状态转移算法原理与应用. 自动化学报, 2020, 46(11): 2260−2274 doi: 10.16383/j.aas.c190624
引用本文: 周晓君, 阳春华, 桂卫华. 状态转移算法原理与应用. 自动化学报, 2020, 46(11): 2260−2274 doi: 10.16383/j.aas.c190624
Zhou Xiao-Jun, Yang Chun-Hua, Gui Wei-Hua. The principle of state transition algorithm and its applications. Acta Automatica Sinica, 2020, 46(11): 2260−2274 doi: 10.16383/j.aas.c190624
Citation: Zhou Xiao-Jun, Yang Chun-Hua, Gui Wei-Hua. The principle of state transition algorithm and its applications. Acta Automatica Sinica, 2020, 46(11): 2260−2274 doi: 10.16383/j.aas.c190624

状态转移算法原理与应用

doi: 10.16383/j.aas.c190624
基金项目: 国家自然科学基金(61873285, 61621062, 61860206014), 111项目(B17048), 湖南省自然科学基金(2018JJ3683)资助
详细信息
    作者简介:

    周晓君:中南大学自动化学院副教授. 2014年获得澳大利亚联邦大学应用数学博士学位. 主要研究方向为复杂工业过程建模、优化与控制, 优化理论与算法, 状态转移算法, 对偶理论及其应用. E-mail: michael.x.zhou@csu.edu.cn

    阳春华:中南大学自动化学院教授. 2002年获得中南大学博士学位. 主要研究方向为复杂工业过程建模与优化, 分析检测与自动化装置, 智能自动化系统. 本文通信作者. E-mail: ychh@csu.edu.cn

    桂卫华:中国工程院院士, 中南大学自动化学院教授. 1981年获得中南矿冶学院硕士学位. 主要研究方向为流程工业智能制造, 复杂工业过程建模, 优化与控制应用和知识自动化. E-mail: gwh@csu.edu.cn

The Principle of State Transition Algorithm and Its Applications

Funds: Supported by the National Natural Science Foundation of China (61873285, 61621062, 61860206014), the 111 Project (B17048) and Hunan Provincial Natural Science Foundation of China (2018JJ3683)
  • 摘要: 状态转移算法是基于状态和状态转移的概念及现代控制理论中状态空间表示法提出的一种智能型随机性全局优化方法, 由于其优良的全局搜索能力和快速收敛性, 在许多优化问题中得到了很好的应用. 本文系统地阐述了状态转移算法的基本原理和内在特性, 详细介绍了状态转移算法的演变与提升, 包括离散、约束与多目标状态转移算法, 状态转移算法参数分析与优化、算子拓展与智能化策略等内容, 并从非线性系统辨识、工业过程控制、机器学习与数据挖掘等方面重点介绍了状态转移算法的应用.
  • 图  1  状态变换算子快速性示意图

    Fig.  1  The rapidity of state transformation operators

    图  2  旋转变换算子可控示意图

    Fig.  2  The controllability of rotation transformation operator

    图  3  轴向搜索变换算子可控示意图

    Fig.  3  The controllability of axesion transformation operator

    图  4  下标表示法示意图

    Fig.  4  Illustration of subscript representation

    图  5  离散状态变换算子示意图

    Fig.  5  Illustration of discrete state transformation operators

    图  6  “二次状态转移” 策略

    Fig.  6  “Second transition” strategy

    图  7  “冒险与恢复” 策略

    Fig.  7  “Risk and restoration in probability” strategy

    图  8  “停滞回溯” 策略

    Fig.  8  “Stagnation backtracking” strategy

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  • 收稿日期:  2019-09-03
  • 录用日期:  2019-12-15
  • 网络出版日期:  2020-01-17
  • 刊出日期:  2020-11-24

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