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Author | : Jairo Jose Espinosa Oviedo |
Publisher | : Springer Science & Business Media |
Total Pages | : 296 |
Release | : 2004-12-03 |
Genre | : Technology & Engineering |
ISBN | : 9781852338282 |
Download Fuzzy Logic, Identification and Predictive Control Book in PDF, ePub and Kindle
Modern industrial processes and systems require adaptable advanced control protocols able to deal with circumstances demanding "judgement” rather than simple "yes/no”, "on/off” responses: circumstances where a linguistic description is often more relevant than a cut-and-dried numerical one. The ability of fuzzy systems to handle numeric and linguistic information within a single framework renders them efficacious for this purpose. Fuzzy Logic, Identification and Predictive Control first shows you how to construct static and dynamic fuzzy models using the numerical data from a variety of real industrial systems and simulations. The second part exploits such models to design control systems employing techniques like data mining. This monograph presents a combination of fuzzy control theory and industrial serviceability that will make a telling contribution to your research whether in the academic or industrial sphere and also serves as a fine roundup of the fuzzy control area for the graduate student.
Author | : Jairo Jose Espinosa Oviedo |
Publisher | : Springer Science & Business Media |
Total Pages | : 274 |
Release | : 2007-01-04 |
Genre | : Technology & Engineering |
ISBN | : 1846280877 |
Download Fuzzy Logic, Identification and Predictive Control Book in PDF, ePub and Kindle
Modern industrial processes and systems require adaptable advanced control protocols able to deal with circumstances demanding "judgement” rather than simple "yes/no”, "on/off” responses: circumstances where a linguistic description is often more relevant than a cut-and-dried numerical one. The ability of fuzzy systems to handle numeric and linguistic information within a single framework renders them efficacious for this purpose. Fuzzy Logic, Identification and Predictive Control first shows you how to construct static and dynamic fuzzy models using the numerical data from a variety of real industrial systems and simulations. The second part exploits such models to design control systems employing techniques like data mining. This monograph presents a combination of fuzzy control theory and industrial serviceability that will make a telling contribution to your research whether in the academic or industrial sphere and also serves as a fine roundup of the fuzzy control area for the graduate student.
Author | : Jairo Jose Espinosa Oviedo |
Publisher | : Springer |
Total Pages | : 264 |
Release | : 2009-10-12 |
Genre | : Technology & Engineering |
ISBN | : 9781848007758 |
Download Fuzzy Logic, Identification and Predictive Control Book in PDF, ePub and Kindle
Modern industrial processes and systems require adaptable advanced control protocols able to deal with circumstances demanding "judgement” rather than simple "yes/no”, "on/off” responses: circumstances where a linguistic description is often more relevant than a cut-and-dried numerical one. The ability of fuzzy systems to handle numeric and linguistic information within a single framework renders them efficacious for this purpose. Fuzzy Logic, Identification and Predictive Control first shows you how to construct static and dynamic fuzzy models using the numerical data from a variety of real industrial systems and simulations. The second part exploits such models to design control systems employing techniques like data mining. This monograph presents a combination of fuzzy control theory and industrial serviceability that will make a telling contribution to your research whether in the academic or industrial sphere and also serves as a fine roundup of the fuzzy control area for the graduate student.
Author | : Robert Babuška |
Publisher | : Springer Science & Business Media |
Total Pages | : 269 |
Release | : 2012-12-06 |
Genre | : Mathematics |
ISBN | : 9401148686 |
Download Fuzzy Modeling for Control Book in PDF, ePub and Kindle
Rule-based fuzzy modeling has been recognised as a powerful technique for the modeling of partly-known nonlinear systems. Fuzzy models can effectively integrate information from different sources, such as physical laws, empirical models, measurements and heuristics. Application areas of fuzzy models include prediction, decision support, system analysis, control design, etc. Fuzzy Modeling for Control addresses fuzzy modeling from the systems and control engineering points of view. It focuses on the selection of appropriate model structures, on the acquisition of dynamic fuzzy models from process measurements (fuzzy identification), and on the design of nonlinear controllers based on fuzzy models. To automatically generate fuzzy models from measurements, a comprehensive methodology is developed which employs fuzzy clustering techniques to partition the available data into subsets characterized by locally linear behaviour. The relationships between the presented identification method and linear regression are exploited, allowing for the combination of fuzzy logic techniques with standard system identification tools. Attention is paid to the trade-off between the accuracy and transparency of the obtained fuzzy models. Control design based on a fuzzy model of a nonlinear dynamic process is addressed, using the concepts of model-based predictive control and internal model control with an inverted fuzzy model. To this end, methods to exactly invert specific types of fuzzy models are presented. In the context of predictive control, branch-and-bound optimization is applied. The main features of the presented techniques are illustrated by means of simple examples. In addition, three real-world applications are described. Finally, software tools for building fuzzy models from measurements are available from the author.
Author | : Janos Abonyi |
Publisher | : Springer Science & Business Media |
Total Pages | : 279 |
Release | : 2012-12-06 |
Genre | : Technology & Engineering |
ISBN | : 146120027X |
Download Fuzzy Model Identification for Control Book in PDF, ePub and Kindle
This book presents new approaches to constructing fuzzy models for model-based control. Simulated examples and real-world applications from chemical and process engineering illustrate the main methods and techniques. Supporting MATLAB and Simulink files create a computational platform for exploration of the concepts and algorithms.
Author | : Huaguang Zhang |
Publisher | : Springer Science & Business Media |
Total Pages | : 423 |
Release | : 2007-10-17 |
Genre | : Technology & Engineering |
ISBN | : 081764539X |
Download Fuzzy Modeling and Fuzzy Control Book in PDF, ePub and Kindle
Fuzzy logic methodology has proven effective in dealing with complex nonlinear systems containing uncertainties that are otherwise difficult to model. Technology based on this methodology is applicable to many real-world problems, especially in the area of consumer products. This book presents the first comprehensive, unified treatment of fuzzy modeling and fuzzy control, providing tools for the control of complex nonlinear systems. Coverage includes model complexity, model precision, and computing time. This is an excellent reference for electrical, computer, chemical, industrial, civil, manufacturing, mechanical and aeronautical engineers, and also useful for graduate courses in electrical engineering, computer engineering, and computer science.
Author | : Mary Margaret Bourke |
Publisher | : |
Total Pages | : 724 |
Release | : 1995 |
Genre | : |
ISBN | : |
Download Self-learning Predictive Control Using Relational-based Fuzzy Logic Book in PDF, ePub and Kindle
Author | : Rómulo Antão |
Publisher | : Springer |
Total Pages | : 136 |
Release | : 2017-07-23 |
Genre | : Technology & Engineering |
ISBN | : 9811046336 |
Download Type-2 Fuzzy Logic Book in PDF, ePub and Kindle
This book focuses on a particular domain of Type-2 Fuzzy Logic, related to process modeling and control applications. It deepens readers’understanding of Type-2 Fuzzy Logic with regard to the following three topics: using simpler methods to train a Type-2 Takagi-Sugeno Fuzzy Model; using the principles of Type-2 Fuzzy Logic to reduce the influence of modeling uncertainties on a locally linear n-step ahead predictor; and developing model-based control algorithms according to the Generalized Predictive Control principles using Type-2 Fuzzy Sets. Throughout the book, theory is always complemented with practical applications and readers are invited to take their learning process one step farther and implement their own applications using the algorithms’ source codes (provided). As such, the book offers avaluable referenceguide for allengineers and researchers in the field ofcomputer science who are interested in intelligent systems, rule-based systems and modeling uncertainty.
Author | : John H. Lilly |
Publisher | : John Wiley & Sons |
Total Pages | : 199 |
Release | : 2011-03-10 |
Genre | : Technology & Engineering |
ISBN | : 1118097815 |
Download Fuzzy Control and Identification Book in PDF, ePub and Kindle
This book gives an introduction to basic fuzzy logic and Mamdani and Takagi-Sugeno fuzzy systems. The text shows how these can be used to control complex nonlinear engineering systems, while also also suggesting several approaches to modeling of complex engineering systems with unknown models. Finally, fuzzy modeling and control methods are combined in the book, to create adaptive fuzzy controllers, ending with an example of an obstacle-avoidance controller for an autonomous vehicle using modus ponendo tollens logic.
Author | : |
Publisher | : DIANE Publishing |
Total Pages | : 26 |
Release | : 2000 |
Genre | : |
ISBN | : 1428996427 |
Download Self-Tuning of Design Variables for Generalized Predictive Control Book in PDF, ePub and Kindle