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Fuzzy Control and Modeling: Analytical Foundations and Applications, by Hao Ying
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The emerging, powerful fuzzy control paradigm has led to the worldwide success of countless commercial products and real-world applications. Fuzzy control is exceptionally practical and cost-effective due to its unique ability to accomplish tasks without knowing the mathematical model of the system, even if it is nonlinear, time varying and complex. Nevertheless, compared with the conventional control technology, most fuzzy control applications are developed in an ad hoc manner with little analytical understanding and without rigorous system analysis and design.
Fuzzy Control and Modeling is the only book that establishes the analytical foundations for fuzzy control and modeling in relation to the conventional linear and nonlinear theories of control and systems. The coverage is up-to-date, comprehensive, in-depth and rigorous. Numeric examples and applications illustrate the utility of the theoretical development.
Important topics discussed include:
- Structures of fuzzy controllers/models with respect to conventional fuzzy controllers/models
- Analysis of fuzzy control and modeling in relation to their classical counterparts
- Stability analysis of fuzzy systems and design of fuzzy control systems
- Sufficient and necessary conditions on fuzzy systems as universal approximators
- Real-time fuzzy control systems for treatment of life-critical problems in biomedicine
- Sales Rank: #6478008 in Books
- Published on: 2000-08-15
- Original language: English
- Number of items: 1
- Dimensions: 10.14" h x .91" w x 7.26" l, 1.79 pounds
- Binding: Hardcover
- 342 pages
From the Back Cover
The emerging, powerful fuzzy control paradigm has led to the worldwide success of countless commercial products and real-world applications. Fuzzy control is exceptionally practical and cost-effective due to its unique ability to accomplish tasks without knowing the mathematical model of the system, even if it is nonlinear, time varying, and complex. Nevertheless, compared with the conventional control technology, most fuzzy control applications are developed in an ad hoc manner with little analytical understanding and without rigorous system analysis and design. Fuzzy Control and Modeling is the only book that establishes the analytical foundations for fuzzy control and modeling in relation to the conventional linear and nonlinear theories of control and systems. The coverage is up-to-date, comprehensive, in-depth, and rigorous. The utility of the theoretical development is illustrated by numeric examples and applications.
In the foreword to Fuzzy Control and Modeling, Professor Lotfi Zadeh, the founder of fuzzy logic, declares: "Professor Ying's book contains much that is new, important, and detailed.... His linkage of basic theory to real-world applications is very impressive.... The last chapter in the book deals with a subject in which Professor Ying is a foremost authority, namely, application of fuzzy control to biomedical systems.... Professor Ying's work should go a long way toward countering the view that fuzzy control is a collection of applications without a solid theory. The deep theory of fuzzy control developed by Professor Ying is of great importance both as a theory and as a foundation for major advances in applications of fuzzy control in industry, biomedicine, and other fields."
Important topics discussed include:
- Structures of fuzzy controllers/models with respect to conventional controllers/models
- Analysis of fuzzy control and modeling in relation to their conventional counterparts
- Stability analysis of fuzzy systems and design of fuzzy control systems
- Sufficient and necessary conditions on fuzzy systems as universal approximators
- Real-time fuzzy control systems for treatment of life-critical problems in biomedicine
Fuzzy Control and Modeling is self-contained and is an invaluable resource for professionals and students in diverse technical fields, who desire to analytically study fuzzy control and modeling.
About the Author
Hao Ying is an associate professor in the Department of Electrical and Computer Engineering at Wayne State University, after leaving the faculty of University of Texas Medical Branch in 2000. Dr. Ying began fuzzy control research in 1981. In 1987 he established the world's first analytical connection between a fuzzy controller and a conventional controller. In 1989 he developed the world's first clinical fuzzy control application-real-time control of blood pressure. He has been making systematic contributions to analytical issues fundamental to fuzzy control and systems.
Most helpful customer reviews
0 of 3 people found the following review helpful.
Needs to define terms and nomenclature up front and stick with it. Has to be a better book available.
By Pat Finder
I am using this book in a graduate college class.
The author flows freely from Fuzzy Mathematics (e.g. Fuzzy Set Theory) to Fuzzy Controllers. Each use different letters.
To add to the confusion, yet another set of variables are used to represent the difference between continuous and discrete controllers.
So, you have 4 different sets of nomenclature used. If you are an applications engineer, you only care about one set: discrete controllers.
Not confused enough? The membership function uses the Greek letter mu (looks like the letter "u"), and the input to the controller uses the letter "u". You ~really~ have to stop and think when you are reading the equations. However, I think this is just where standard Fuzzy nomenclature bumps into standard Control Theory nomenclature.
It would have been very helpful to have a diagram of the system up front, with all the variables labeled.
Chapter 7 discusses using Fuzzy Systems to approximate continuous functions. I haven't survived the book to that point yet, but why would you want to do that? The whole reason to use fuzzy logic is to handle discontinuous, and non-linear situations, which cannot be handled by other means. Function approximation can be easily done using Taylor's series, Lagrangians, etc...
I also feel it necessary to add that as a first time reader to the book, who had never read the book before, and who is reading the book for the first time now for the first time.... that there are many places in the book where redundancies are used overly redundantly.
The redundancies are a problem because they add confusion to a difficult subject.
Ex: p29: "Our answer is from the viewpoint of conventional control technology, and it reveals the nature of fuzzy control in relation to conventional control."
There were 14 editors on this book, but it still could have been edited better. (e.g. Editing was a bit fUzZY, and not fussy enough.)
The book provides no example code or software. So, if you want to implement anything, you are on your own. There has to be a better book on Fuzzy Logic around. If there isn't, then there is an opportunity.
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