《智能控制技术与应用案例设计》聚焦智能控制技术在石化行业的应用，全书共六章。首章阐述智能控制的发展、研究内容、对象、性能及特点。第二章围绕模糊控制，涵盖理论、模糊PID、Matlab 实现及工程实验。第三章将李雅普诺夫稳定性理论融入自适应控制，解决非线性系统问题并给出仿真实例。第四章构建神经网络系统辨识体系，用于流程工业过程建模。第五章研究遗传算法与群智能搜索在系统辨识中的融合应用。第六章介绍专家控制系统的构建、分类及应用。本书融合多学科知识，提供理论框架与实践案例，助力提升工业生产智能化水平。

第 1 章 绪论 ···································································································1
1.1 智能控制的提出与发展 ·············································································1
1.1.1 智能控制的提出··············································································1
1.1.2 智能控制的发展··············································································3
1.2 智能控制的主要研究内容 ··········································································3
1.2.1 专家控制·······················································································4
1.2.2 模糊控制·······················································································4
1.2.3 神经网络控制·················································································5
1.2.4 自适应控制····················································································6
1.2.5 生物启发算法·················································································7
1.3 智能控制的研究对象、性能及特点 ······························································8
1.3.1 智能控制的研究对象 ·······································································8
1.3.2 智能控制系统的性能及特点 ······························································8
第 2 章 模糊控制 ··························································································.10
2.1 模糊理论概述·······················································································.10
2.1.1 模糊理论问题的引入 ····································································.10
2.1.2 模糊理论问题的发展 ····································································.10
2.1.3 模糊理论的应用领域 ····································································.11
2.2 模糊控制和模糊 PID 控制 ·······································································.12
2.2.1 模糊控制····················································································.12
2.2.2 模糊控制系统··············································································.13
2.2.3 模糊 PID 控制 ·············································································.14
2.2.4 模糊 PID 控制器的设计过程 ···························································.16
2.3 2.4 基于 Matlab 的模糊控制器设计 ································································.23
模糊 PID 工程实验 ················································································.26
2.4.1 换热器模糊 PID 控制实验目的 ························································.26
2.4.2 换热器模糊 PID 控制实验要求 ························································.26
2.4.3 换热器模糊 PID 控制实验设备 ························································.26
2.4.4 换热器模糊 PID 控制实验内容 ························································.27
2.4.5 换热器模糊 PID 控制实验结论 ························································.39
2.5 模糊控制的适用范围及研究意义 ······························································.40
第 3 章 基于自适应方法的非线性控制系统设计与实现 ··········································.42
3.1 自校正控制系统····················································································.42
3.2 李雅普诺夫稳定性定理 ··········································································.45
3.2.1 李雅普诺夫意义下的稳定性 ···························································.45
3.2.2 函数的正定性··············································································.46
3.2.3 李雅普诺夫稳定性定理内容 ···························································.46
3.3 一类非线性动态的自适应控制与稳定性 ·····················································.48
3.3.1 问题描述····················································································.48
3.3.2 统一的维纳结构···········································································.49
3.3.3 非线性动态过程建模中的简化维纳结构 ············································.51
3.3.4 自适应控制设计与参数估计 ···························································.52
3.3.5 跟踪性能及稳定性分析 ·································································.54
3.3.6 仿真实例····················································································.56
3.4 最小方差调节器和最小方差自校正调节器设计 ············································.65
3.5 自适应控制的适用范围及研究意义 ···························································.68
第 4 章 基于神经网络的流程工业过程建模 ·························································.70
4.1 普通神经网络与线性系统辨识的关系 ························································.70
4.1.1 问题描述····················································································.70
4.1.2 基础理论····················································································.72
4.1.3 NN2TF 算法················································································.75
4.2 循环神经网络在过程建模中的应用 ···························································.78
4.2.1 问题描述····················································································.78
4.2.2 模型介绍····················································································.81
4.2.3 DRNN 辨识模型的学习算法 ···························································.87
4.2.4 基于李雅普诺夫稳定性方法的自适应学习率推导 ································.88
4.3 GRU 神经网络在非线性动态过程建模中的应用 ···········································.91
4.3.1 GRU 神经网络概述 ······································································.91
4.3.2 基于 GRU 神经网络的过程建模·······················································.91
4.4 神经网络的适用范围及研究意义 ····························································.105
第 5 章 基于生物启发算法的辨识与控制优化 ······················································106
5.1 遗传算法介绍·····················································································.106
5.1.1 遗传算法概念、特点及应用 ·························································.106
5.1.2 遗传算法的基本流程及实现技术 ···················································.107
5.2 群智能搜索在系统辨识中的典型应用 ······················································.108
5.2.1 问题描述··················································································.108
5.2.2 基础理论··················································································.109
5.2.3 基于群智能的迭代辨识 ·································································111
5.2.4 仿真实例····················································································115
5.3 生物启发算法的适用范围及研究意义 ······················································.121
第 6 章 专家控制系统 ····················································································123
6.1 专家系统···························································································.123
6.1.1 专家系统定义············································································.123
6.1.2 专家系统构造············································································.123
6.1.3 专家系统实现方式······································································.124
6.1.4 专家系统工作过程······································································.124
6.1.5 基于专家系统的自整定 PID 控制器 ················································.125
6.2 专家控制系统介绍 ··············································································.128
6.2.1 直接专家控制系统······································································.128
6.2.2 间接专家控制系统······································································.129
6.2.3 专家 PID 控制 ···········································································.130
6.3 专家控制系统的适用范围及研究意义 ······················································.131
参考文献······································································································132