دانلود پایان نامه ارشد
عنوان :
High dimensional neural fuzzy controller for
nonlinear systems
زبان : انگلیسی
سال انتشار : 2007
در زمینه : مهندسی برق
کد محصول : 1203
تعداد صفحات :86
قیمت :15000 تومان
چکیده انگلیسی :
Today, the control theory plays a significant role in almost every field of science and engineering. The classical theory of automatic control systems has been widely used in modern society and it ranges from simple application, such as in washing machine control systems, to highly sophisticated systems such as space shuttles, satellites and intelligent robots. Throughout the history of control, the goal has been to mimic the human worker interacting with machines and to process events without human interaction. In recent years, researchers work to design controllers that have the ability to "learn" and "think" like human expert. Fuzzy theory is a powerful problem-solving method with wide applications in industrial control and information processing [3] [4] [5]. It provides a simple way to draw definite conclusions from vague, ambiguous and imprecise information. Unlike classic approach which needs a deep understanding of system dynamics and the knowledge of exact equations and precise numerical values, fuzzy logic incorporates simple rule-based "IF X AND Y THEN Z" approach to solve control problem rather than trying to model it mathematically. Fuzzy modeling based on numerical data, which was first explored systematically by Takagi and Sugeno [6], has found many successful applications to complex system modeling. Fuzzy controllers are the most important application of the fuzzy theory. They work rather differently than conventional controllers by using expert knowledge (rules) instead of differential equations to describe a system. The knowledge could be expressed in a natural way with "linguistic variables", which are described by "fuzzy sets". Fuzzy logic has many advantages but also has some limitations. For example, fuzzy systems needs expert for rule discovery and they cannot learn the rules themselves. Artificial Neural Network (ANN) is an important concept in artificial intelligence. These networks are based on the parallel architecture of human brain. The true power and advantage of neural networks lies in their ability to represent both linear and non-linear relationships and in their capacity to learn these relationships directly from training examples. The training examples must be selected carefully otherwise useful time is wasted or even worse the network might be functioning wrongly. ANN is made of many highly interconnected processing elements (neurons) working in unison to solve specific problems. It can create its own organisation or representation of the information it receives during learning time but the knowledge represented by the network is difficult to understand. Also, the mathematical theories used to guarantee the performance of an applied neural network are still under development.
با تشکر
ieeeproject
این وبلاگ توسط جمعی از دانشجویان ارشد و دکتری در زمینه مهندسی برق با هدف تبادل اطلاعات و فروش محصولات دانش بنیان با قیمتی مناسب راه اندازی شده است.در این وبلاگ مطالب زیر برای فروش قرار داده شده است .