摘 要
随着现代工业技术的快速发展，电气自动化系统在复杂环境下的适应性和控制精度面临新的挑战，传统的精确控制方法难以满足不确定性和非线性系统的控制需求。为此，本文提出了一种基于模糊控制的电气自动化系统设计方案，旨在通过引入模糊逻辑理论提升系统的鲁棒性和智能化水平。研究中采用模糊控制器替代传统PID控制器，结合隶属度函数和模糊推理规则，实现了对复杂动态过程的有效控制。同时，为优化模糊控制器参数，引入遗传算法进行自适应调整，从而进一步提高控制性能。实验结果表明，该系统在面对不确定性因素时表现出更强的适应能力，控制误差显著降低，响应速度明显加快。与传统方法相比，本研究提出的方案在稳定性、精确性和灵活性方面均具有明显优势。
关键词：模糊控制 遗传算法 电气自动化系统
Abstract
With the rapid development of modern industrial technology, the adaptability and control accuracy of electrical automation system in complex environment are facing new challenges, and the traditional precise control method is difficult to meet the control requirements of uncertain and nonlinear system. In this paper, an electrical automation system based on fuzzy control is designed to improve the robustness and intelligence level of the system by introducing fuzzy logic theory. Using fuzzy controller to replace the traditional PID controller, combining the membership function and fuzzy inference rules to realize the effective control of complex dynamic process. Meanwhile, to optimize the fuzzy controller parameters, the genetic algorithm is introduced for adaptive adjustment to further improve the control performance. Experimental results show that the system showed greater adaptation in the face of uncertainty factors, with significantly reduced control error and significantly faster response speed. Compared with traditional methods, the proposed scheme has obvious advantages in stability, accuracy and flexibility.
Keyword:Fuzzy Control Genetic Algorithm Electrical Automation System
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状分析 1
1.3本文研究方法概述 1
2模糊控制理论基础 2
2.1模糊控制的基本概念 2
2.2模糊逻辑系统的设计原理 2
2.3模糊控制在电气自动化中的应用价值 3
3基于模糊控制的系统设计方法 3
3.1系统设计的需求分析 3
3.2模糊控制器的设计流程 4
3.3关键参数的优化与调整 4
3.4设计案例分析 5
4系统性能评估与改进策略 5
4.1性能评估指标体系构建 5
4.2实验验证与数据分析 6
4.3系统存在的问题与优化方向 6
4.4改进后的效果评估 7
结论 7
参考文献 9
致谢 10
随着现代工业技术的快速发展，电气自动化系统在复杂环境下的适应性和控制精度面临新的挑战，传统的精确控制方法难以满足不确定性和非线性系统的控制需求。为此，本文提出了一种基于模糊控制的电气自动化系统设计方案，旨在通过引入模糊逻辑理论提升系统的鲁棒性和智能化水平。研究中采用模糊控制器替代传统PID控制器，结合隶属度函数和模糊推理规则，实现了对复杂动态过程的有效控制。同时，为优化模糊控制器参数，引入遗传算法进行自适应调整，从而进一步提高控制性能。实验结果表明，该系统在面对不确定性因素时表现出更强的适应能力，控制误差显著降低，响应速度明显加快。与传统方法相比，本研究提出的方案在稳定性、精确性和灵活性方面均具有明显优势。
关键词：模糊控制 遗传算法 电气自动化系统
Abstract
With the rapid development of modern industrial technology, the adaptability and control accuracy of electrical automation system in complex environment are facing new challenges, and the traditional precise control method is difficult to meet the control requirements of uncertain and nonlinear system. In this paper, an electrical automation system based on fuzzy control is designed to improve the robustness and intelligence level of the system by introducing fuzzy logic theory. Using fuzzy controller to replace the traditional PID controller, combining the membership function and fuzzy inference rules to realize the effective control of complex dynamic process. Meanwhile, to optimize the fuzzy controller parameters, the genetic algorithm is introduced for adaptive adjustment to further improve the control performance. Experimental results show that the system showed greater adaptation in the face of uncertainty factors, with significantly reduced control error and significantly faster response speed. Compared with traditional methods, the proposed scheme has obvious advantages in stability, accuracy and flexibility.
Keyword:Fuzzy Control Genetic Algorithm Electrical Automation System
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状分析 1
1.3本文研究方法概述 1
2模糊控制理论基础 2
2.1模糊控制的基本概念 2
2.2模糊逻辑系统的设计原理 2
2.3模糊控制在电气自动化中的应用价值 3
3基于模糊控制的系统设计方法 3
3.1系统设计的需求分析 3
3.2模糊控制器的设计流程 4
3.3关键参数的优化与调整 4
3.4设计案例分析 5
4系统性能评估与改进策略 5
4.1性能评估指标体系构建 5
4.2实验验证与数据分析 6
4.3系统存在的问题与优化方向 6
4.4改进后的效果评估 7
结论 7
参考文献 9
致谢 10
