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- Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
- FUZZY CONTROL SYSTEMS DESIGN AND ANALYSIS
- Stability Analysis of Fuzzy-Model-Based Control Systems
- Multivariable Fuzzy Logic Control Systems Design
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
The system can't perform the operation now. Try again later. Citations per year. Duplicate citations. The following articles are merged in Scholar. Their combined citations are counted only for the first article. Merged citations.
This "Cited by" count includes citations to the following articles in Scholar. Add co-authors Co-authors. Upload PDF. Follow this author. New articles by this author. New citations to this author. New articles related to this author's research. Email address for updates. My profile My library Metrics Alerts. Sign in. Get my own profile Cited by View all All Since Citations h-index 53 32 iindex Co-authors Hua O. Wang Boston University Verified email at bu. Motoyasu Tanaka Professor, The Univ.
Automatica Informatica Indust. AI2 , Dept. Eng Verified email at isa. The University of Electro-Communications. Verified email at mce. Articles Cited by Co-authors. Title Sort Sort by citations Sort by year Sort by title.
IEEE transactions on fuzzy systems 4 1 , , IEEE Transactions on fuzzy systems 6 2 , , IEEE Transactions on fuzzy systems 11 4 , , IEEE transactions on robotics 21 4 , , Proceedings of the American Control Conference.
Articles 1—20 Show more. Help Privacy Terms. Stability analysis and design of fuzzy control systems K Tanaka, M Sugeno Fuzzy sets and systems 45 2 , , A robust stabilization problem of fuzzy control systems and its application to backing up control of a truck-trailer K Tanaka, M Sano IEEE Transactions on Fuzzy systems 2 2 , , An introduction to fuzzy logic for practical applications K Tanaka.
Successive identification of a fuzzy model and its applications to prediction of a complex system M Sugeno, K Tanaka Fuzzy sets and systems 42 3 , , Stability analysis of fuzzy control systems using Lyapunov's direct method K Tanaka Proc.
FUZZY CONTROL SYSTEMS DESIGN AND ANALYSIS
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Request PDF | Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach | This chapter starts with the introduction of the.
Stability Analysis of Fuzzy-Model-Based Control Systems
The system can't perform the operation now. Try again later. Citations per year.
This chapter describes widespread methods of model-based fuzzy control systems. The subject of this chapter is a systematic framework for the stability and design of nonlinear fuzzy control systems. We are trying to build a bridge between conventional fuzzy control and classic control theory. By building this bridge, the strong well developed tools of classic control could be used in model-based fuzzy control systems. Model-based fuzzy control, with the possibility of guaranteeing the closed loop stability, is an attractive method for control of nonlinear systems.
This balanced treatment features an overview of fuzzy control modeling and stability analysis as well as a section on the use of linear matrix inequalities lmi as an approach to fuzzy design and control. Fault detection and control co design for discrete time delayed fuzzy networked control systems subject to quantization and multiple packet dropouts fuzzy sets and systems v nc p1 25 january Fuzzy control systems design and analysis. Building on the so called takagi sugeno fuzzy model a number of most important issues in fuzzy control systems are addressed. Fuzzy control systems design and analysis addresses these issues in the framework of parallel distributed compensation a controller structure devised in accordance with the fuzzy model.
A fuzzy control system is a control system based on fuzzy logic —a mathematical system that analyzes analog input values in terms of logical variables that take on continuous values between 0 and 1, in contrast to classical or digital logic, which operates on discrete values of either 1 or 0 true or false, respectively.
Multivariable Fuzzy Logic Control Systems Design
Skip to Main Content. A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. Use of this web site signifies your agreement to the terms and conditions. However, it unfortunately suffers from criticism of lacking of systematic stability analysis and controller design though it has a great success in industry applications.
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fuzzy control systems are addressed. These include stability analysis, system- atic design procedures, incorporation of performance specifications, robust-.