摘 要：随着智能控制技术的快速发展，模糊逻辑作为一种能够有效处理不确定性和复杂性的方法，逐渐成为智能控制系统设计中的重要工具。本研究旨在探讨模糊逻辑在智能控制系统中的应用潜力及其优化策略，通过构建基于模糊推理的控制模型，解决传统精确数学模型难以应对的非线性、不确定性问题。研究采用模糊集合论与专家知识相结合的方法，设计了一种改进型模糊控制器，并通过仿真试验验证其性能。结果表明，该控制器能够在动态环境中实现高精度、快速响应的控制效果，显著提升了系统的鲁棒性和适应能力。本研究的创新点在于提出了一种自适应模糊规则调整机制，使系统具备更强的学习能力和环境适应性，为模糊逻辑在复杂智能控制领域的进一步应用提供了理论支持和技术参考。研究表明，模糊逻辑在提升智能控制系统性能方面具有显著优势，未来可结合深度学习等技术拓展其应用场景。
关键词：模糊逻辑；智能控制系统；模糊控制器；自适应调整机制；仿真试验
Application of Fuzzy Logic in Intelligent Control Systems
英文人名
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Abstract：With the rapid development of intelligent control technologies, fuzzy logic has emerged as a crucial tool in the design of intelligent control systems due to its effectiveness in addressing uncertainties and complexities. This study investigates the application potential of fuzzy logic in intelligent control systems and proposes optimization strategies by constructing a control model based on fuzzy inference to tackle nonlinearities and uncertainties that are difficult for traditional precise mathematical models to handle. By integrating fuzzy set theory with expert knowledge, an improved fuzzy controller was designed and validated through simulation experiments. The results demonstrate that this controller achieves high-precision and rapid-response control performance in dynamic environments, significantly enhancing the robustness and adaptability of the system. A key innovation of this research lies in the introduction of an adaptive fuzzy rule adjustment mechanism, which strengthens the system's learning capabilities and environmental adaptability, providing theoretical support and technical references for further applications of fuzzy logic in complex intelligent control domains. The findings indicate that fuzzy logic offers significant advantages in improving the performance of intelligent control systems and suggest that future research could explore its integration with technologies such as deep learning to broaden its application scope.
Keywords: Fuzzy Logic；Intelligent Control System；Fuzzy Controller；Adaptive Adjustment Mechanism；Simulation Experiment
目 录
引言 1
一、模糊逻辑基础与智能控制概述 1
(一)模糊逻辑的基本原理 1
(二)智能控制系统的特点 2
(三)模糊逻辑在控制中的优势 2
二、模糊逻辑控制器的设计方法 3
(一)控制器结构设计原则 3
(二)模糊规则的建立与优化 3
(三)输入输出变量的模糊化处理 4
三、模糊逻辑在典型智能控制系统中的应用 4
(一)工业过程控制中的应用 4
(二)机器人运动控制中的实现 5
(三)智能交通系统中的案例分析 5
四、模糊逻辑控制系统的性能评估与改进 6
(一)系统性能的评价指标 6
(二)控制精度与鲁棒性分析 6
(三)基于反馈的系统优化策略 7
结论 7
参考文献 9
致谢 9
