Open AccessBook
Industrial applications of fuzzy control
TLDR
This work focuses on the application of Fuzzy and Artificial Intelligence Methods in the Building of a Blast Furnace Smelting Process Model and the development of Performance Adaptive FuzzY Controllers with Application to Continuous Casting Plants.Abstract:
Preface. Automatic Train Operation System by Predictive Fuzzy Control (S. Yasunobu, S. Miyamoto). Application of Fuzzy Reasoning to the Water Purification Process (O. Yagashita, O. Itoh, M. Sugeno). The Application of a Fuzzy Controller to the Control of a Multi-Degree-of-Freedom Robot Arm (E.M. Scharf, N.J. Mandic). Optimizing Control of a Diesel Engine (Y. Murayama et al.). Development of Performance Adaptive Fuzzy Controllers with Application to Continuous Casting Plants (G. Bartolini et al.). A Fuzzy Logic Controller for Aircraft Flight Control (L.I. Larkin). Automobile Speed Control System Using a Fuzzy Logic Controller (S. Murakami, M. Maeda). An Experimental Study on Fuzzy Parking Control Using a Model Car (M. Sugeno, K. Murakami). A Fuzzy Controller in Turning Process Automation (Y. Sakai, K. Ohkusa). Design of Fuzzy Control Algorithms with the Aid of Fuzzy Models (W. Pedrycz). Human Operator's Fuzzy Model in Man-Machine System with a Nonlinear Controlled Object (K. Matsushima, H. Sugiyama). The Influence of Some Parameters on the Accuracy of a Fuzzy Model (J.B. Kiszka, M.E. Kochanska, D.S. Sliwinska). A Microprocessor Based Fuzzy Controller for Industrial Purposes (T. Yamazaki, M. Sugeno). The Application of Fuzzy and Artificial Intelligence Methods in the Building of a Blast Furnace Smelting Process Model (H. Zhao, M. Ma). An Annotated Bibliography of Fuzzy Control (R.M. Tong).read more
Citations
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Journal ArticleDOI
Neuro-fuzzy modeling and control
TL;DR: The essential part of neuro-fuzzy synergisms comes from a common framework called adaptive networks, which unifies both neural networks and fuzzy models, which possess certain advantages over neural networks.
Journal ArticleDOI
A Survey on Analysis and Design of Model-Based Fuzzy Control Systems
TL;DR: A survey on recent developments (or state of the art) of analysis and design of model based fuzzy control systems based on the so-called Takagi-Sugeno fuzzy models or fuzzy dynamic models.
Book
Introduction to Fuzzy Logic using MATLAB
TL;DR: This paper presents a model for a Fuzzy Rule-Based System that automates the very labor-intensive and therefore time-heavy process of decision-making in the context of classical sets.
Journal ArticleDOI
An overview of operators for aggregating information
Zeshui Xu,Qingli Da +1 more
TL;DR: This work first makes a survey of the existing main aggregation operators and then proposes some new aggregation operators such as the induced ordered weighted geometric averaging (IOWGA) operator, generalized inducedordered weighted averaging (GIOWA), hybrid weighted averaged (HWA), etc., and briefly classify all of these aggregation operators.
Book
Possibilistic logic
D. Dubois,Jérôme Lang,H. Prade +2 more
TL;DR: Possibilistic logic is a logic of uncertainty tailored for reasoning under incomplete evidence and partially inconsistent knowledge that handles formulas of propositional or first-order logic to which are attached numbers between 0 and 1.
References
More filters
Journal ArticleDOI
Neuro-fuzzy modeling and control
TL;DR: The essential part of neuro-fuzzy synergisms comes from a common framework called adaptive networks, which unifies both neural networks and fuzzy models, which possess certain advantages over neural networks.
Journal ArticleDOI
A Survey on Analysis and Design of Model-Based Fuzzy Control Systems
TL;DR: A survey on recent developments (or state of the art) of analysis and design of model based fuzzy control systems based on the so-called Takagi-Sugeno fuzzy models or fuzzy dynamic models.
Book
Introduction to Fuzzy Logic using MATLAB
TL;DR: This paper presents a model for a Fuzzy Rule-Based System that automates the very labor-intensive and therefore time-heavy process of decision-making in the context of classical sets.
Journal ArticleDOI
An overview of operators for aggregating information
Zeshui Xu,Qingli Da +1 more
TL;DR: This work first makes a survey of the existing main aggregation operators and then proposes some new aggregation operators such as the induced ordered weighted geometric averaging (IOWGA) operator, generalized inducedordered weighted averaging (GIOWA), hybrid weighted averaged (HWA), etc., and briefly classify all of these aggregation operators.
Book
Possibilistic logic
D. Dubois,Jérôme Lang,H. Prade +2 more
TL;DR: Possibilistic logic is a logic of uncertainty tailored for reasoning under incomplete evidence and partially inconsistent knowledge that handles formulas of propositional or first-order logic to which are attached numbers between 0 and 1.