Fuzzy Logic, Identification and Predictive Control - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Fuzzy Logic, Identification and Predictive Control write by Jairo Jose Espinosa Oviedo. This book was released on 2007-01-04. Fuzzy Logic, Identification and Predictive Control available 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.
Fuzzy Logic, Identification and Predictive Control
Fuzzy Logic, Identification and Predictive Control - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Fuzzy Logic, Identification and Predictive Control write by Jairo Jose Espinosa Oviedo. This book was released on 2009-10-12. Fuzzy Logic, Identification and Predictive Control available 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.
Fuzzy Model Identification for Control
Fuzzy Model Identification for Control - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Fuzzy Model Identification for Control write by Janos Abonyi. This book was released on 2012-12-06. Fuzzy Model Identification for Control available 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.
Fuzzy Modeling for Control
Fuzzy Modeling for Control - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Fuzzy Modeling for Control write by Robert Babuška. This book was released on 2012-12-06. Fuzzy Modeling for Control available 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.
Fuzzy Modeling and Fuzzy Control
Fuzzy Modeling and Fuzzy Control - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Fuzzy Modeling and Fuzzy Control write by Huaguang Zhang. This book was released on 2007-10-17. Fuzzy Modeling and Fuzzy Control available 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.
