第5章 Perspectives on Fuzzy Control 教学内容 本章讲述模糊控制与传统控制的相互关系、模糊神经网络控制、模糊控制和遗传算法的相互联系与区别、 模糊控制与基于知识系统的交叉和融合。 教学重点 重点内容是讲述模糊控制与传统控制的相互关系,模糊系统与神经网络、遗传算法、基于知识的学习系 统的相互联系以及交叉融合。 教学难点 对模糊控制与传统控制、神经网络控制、遗传算法以及基于知识的系统的区别和联系的准确把握和理 解,学会用发展和联系的观点看待智能控制学科的发展。 教学要求 要求学生基本了解模糊控制与传统控制、神经网络控制、遗传算法以及基于知识的系统的区别和联系. 通过本章的学习,进一步加深对智能控制特点的理解,学会用发展和联系的观点看待智能控制学科的发展 从而培养学生创常新意识和能力,形成正确的工作方法。 5.1 Overview Fuzzy control does not exist as an isolated topic devoid of relationships to other fields, and it is important to understand how it relates to these other fields in order to strengthen your understanding of it. We have emphasized that fuzzy control has its foundations in conventional control and that there are many relationships to techniques, ideas, and methodologies there. Fuzzy control is also an"intelligent control"technique, and hence there are certain relationships between it and other intelligent control methods. In this chapter we will provide a brief overview of some of the basic relationships between fuzzy control and other control methods. This will give the reader who has a good understanding of fuzzy control a glimpse of related topics in other areas. Moreover, it will give the reader who has a good understanding of other areas of control an idea of what the field of fuzzy control is concerned with We begin the chapter in Section 5.2 by providing a conventional control engineering perspective on fuzzy control This is essentially a summary of many of the points that we have made throughout the text, but here we bring them all together. Following this, in Section 5.3 we introduce two popular areas in neural networks, the multilayer perceptron and the radial basis function neural network. We explain that a class of radial basis function neural networks is identical to a class of fuzzy systems. Moreover, we explain how techniques covered in this book(e.g, gradient training and adaptive control) can be used for neural networks. In Section 5. 4 we explain genetic algorithms, their relationship to the field of control, and particularly their use with fuzzy systems. Next, in Section 5.5 we provide an overview of some of the relationships to knowledge-based systems, particularly expert systems(and hence expert control) and planning systems第 5 章 Perspectives on Fuzzy Control 教学内容 本章讲述模糊控制与传统控制的相互关系、模糊神经网络控制、模糊控制和遗传算法的相互联系与区别、 模糊控制与基于知识系统的交叉和融合。 教学重点 重点内容是讲述模糊控制与传统控制的相互关系，模糊系统与神经网络、遗传算法、基于知识的学习系 统的相互联系以及交叉融合。 教学难点 对模糊控制与传统控制、神经网络控制、遗传算法以及基于知识的系统的区别和联系的准确把握和理 解，学会用发展和联系的观点看待智能控制学科的发展。 教学要求 要求学生基本了解模糊控制与传统控制、神经网络控制、遗传算法以及基于知识的系统的区别和联系。 通过本章的学习，进一步加深对智能控制特点的理解，学会用发展和联系的观点看待智能控制学科的发展， 从而培养学生创常新意识和能力，形成正确的工作方法。 5.1 Overview Fuzzy control does not exist as an isolated topic devoid of relationships to other fields, and it is important to understand how it relates to these other fields in order to strengthen your understanding of it. We have emphasized that fuzzy control has its foundations in conventional control and that there are many relationships to techniques, ideas, and methodologies there. Fuzzy control is also an "intelligent control" technique, and hence there are certain relationships between it and other intelligent control methods. In this chapter we will provide a brief overview of some of the basic relationships between fuzzy control and other control methods. This will give the reader who has a good understanding of fuzzy control a glimpse of related topics in other areas. Moreover, it will give the reader who has a good understanding of other areas of control an idea of what the field of fuzzy control is concerned with. We begin the chapter in Section 5.2 by providing a conventional control engineering perspective on fuzzy control. This is essentially a summary of many of the points that we have made throughout the text, but here we bring them all together. Following this, in Section 5.3 we introduce two popular areas in neural networks, the multilayer perceptron and the radial basis function neural network. We explain that a class of radial basis function neural networks is identical to a class of fuzzy systems. Moreover, we explain how techniques covered in this book (e.g., gradient training and adaptive control) can be used for neural networks. In Section 5.4 we explain genetic algorithms, their relationship to the field of control, and particularly their use with fuzzy systems. Next, in Section 5.5 we provide an overview of some of the relationships to knowledge-based systems, particularly expert systems (and hence expert control) and planning systems