基于智能算法的电机参数辨识与优化控制研究
摘要
电机参数辨识与优化控制是现代工业自动化领域的重要研究方向，针对传统电机参数辨识方法存在精度低、适应性差等问题，本文基于智能算法开展电机参数辨识与优化控制研究。以提高电机参数辨识精度和优化控制效果为目的，选取遗传算法、粒子群算法等智能算法作为研究工具，构建了基于智能算法的电机参数辨识模型，该模型能够根据电机运行数据自动调整参数，实现对电机参数的高精度辨识；同时设计了基于智能算法的优化控制策略，通过建立电机运行状态与控制目标之间的映射关系，实现了对电机运行过程的有效控制。实验结果表明，所提方法在不同工况下均能准确辨识电机参数，且优化控制后的电机性能指标明显优于传统方法，如响应速度更快、稳态误差更小等。本文创新性地将智能算法应用于电机参数辨识与优化控制中，为解决传统方法存在的问题提供了新思路，对提升电机系统的智能化水平具有重要意义。
关键词：电机参数辨识；智能算法；优化控制
Abstract
Parameter identification and optimal control of electric motors are crucial research directions in modern industrial automation. Addressing the issues of low accuracy and poor adaptability associated with traditional motor parameter identification methods, this study investigates motor parameter identification and optimization control based on intelligent algorithms. Aiming to enhance the accuracy of motor parameter identification and improve control performance, this research employs intelligent algorithms such as genetic algorithms and particle swarm optimization as tools. A motor parameter identification model based on intelligent algorithms has been constructed, which can automatically adjust parameters according to motor operation data, achieving high-precision identification of motor parameters. Simultaneously, an optimization control strategy based on intelligent algorithms has been designed, establishing a mapping relationship between motor operating states and control ob jectives, thereby realizing effective control of the motor operation process. Experimental results demonstrate that the proposed method can accurately identify motor parameters under various operating conditions, and the performance metrics of the motor after optimization control are significantly superior to those achieved by traditional methods, exhibiting faster response speeds and smaller steady-state errors. This paper innovatively applies intelligent algorithms to motor parameter identification and optimization control, providing new insights into solving problems inherent in traditional methods and contributing significantly to enhancing the intelligence level of motor systems.
Keywords：Motor Parameter Identification; Intelligent Algorithm; Optimal Control
目 录
摘要 I
Abstract II
一、绪论 1
(一) 研究背景与意义 1
(二) 国内外研究现状 1
(三) 研究方法概述 2
二、智能算法在电机参数辨识中的应用 2
(一) 参数辨识的重要性 2
(二) 常用智能算法分析 3
(三) 智能算法的改进与优化 3
三、电机参数辨识模型构建 4
(一) 辨识模型的数学基础 4
(二) 模型构建的关键技术 5
(三) 模型验证与误差分析 6
四、基于智能算法的电机优化控制策略 7
(一) 控制策略的设计原则 7
(二) 智能控制算法的选择 8
(三) 控制效果评估与改进 8
结 论 10
参考文献 11
摘要
电机参数辨识与优化控制是现代工业自动化领域的重要研究方向，针对传统电机参数辨识方法存在精度低、适应性差等问题，本文基于智能算法开展电机参数辨识与优化控制研究。以提高电机参数辨识精度和优化控制效果为目的，选取遗传算法、粒子群算法等智能算法作为研究工具，构建了基于智能算法的电机参数辨识模型，该模型能够根据电机运行数据自动调整参数，实现对电机参数的高精度辨识；同时设计了基于智能算法的优化控制策略，通过建立电机运行状态与控制目标之间的映射关系，实现了对电机运行过程的有效控制。实验结果表明，所提方法在不同工况下均能准确辨识电机参数，且优化控制后的电机性能指标明显优于传统方法，如响应速度更快、稳态误差更小等。本文创新性地将智能算法应用于电机参数辨识与优化控制中，为解决传统方法存在的问题提供了新思路，对提升电机系统的智能化水平具有重要意义。
关键词：电机参数辨识；智能算法；优化控制
Abstract
Parameter identification and optimal control of electric motors are crucial research directions in modern industrial automation. Addressing the issues of low accuracy and poor adaptability associated with traditional motor parameter identification methods, this study investigates motor parameter identification and optimization control based on intelligent algorithms. Aiming to enhance the accuracy of motor parameter identification and improve control performance, this research employs intelligent algorithms such as genetic algorithms and particle swarm optimization as tools. A motor parameter identification model based on intelligent algorithms has been constructed, which can automatically adjust parameters according to motor operation data, achieving high-precision identification of motor parameters. Simultaneously, an optimization control strategy based on intelligent algorithms has been designed, establishing a mapping relationship between motor operating states and control ob jectives, thereby realizing effective control of the motor operation process. Experimental results demonstrate that the proposed method can accurately identify motor parameters under various operating conditions, and the performance metrics of the motor after optimization control are significantly superior to those achieved by traditional methods, exhibiting faster response speeds and smaller steady-state errors. This paper innovatively applies intelligent algorithms to motor parameter identification and optimization control, providing new insights into solving problems inherent in traditional methods and contributing significantly to enhancing the intelligence level of motor systems.
Keywords：Motor Parameter Identification; Intelligent Algorithm; Optimal Control
目 录
摘要 I
Abstract II
一、绪论 1
(一) 研究背景与意义 1
(二) 国内外研究现状 1
(三) 研究方法概述 2
二、智能算法在电机参数辨识中的应用 2
(一) 参数辨识的重要性 2
(二) 常用智能算法分析 3
(三) 智能算法的改进与优化 3
三、电机参数辨识模型构建 4
(一) 辨识模型的数学基础 4
(二) 模型构建的关键技术 5
(三) 模型验证与误差分析 6
四、基于智能算法的电机优化控制策略 7
(一) 控制策略的设计原则 7
(二) 智能控制算法的选择 8
(三) 控制效果评估与改进 8
结 论 10
参考文献 11
