System Identification for Self-adaptive Control
Author: W. D. T. Davies
Publisher: John Wiley & Sons
Published: 1970
Total Pages: 404
ISBN-13:
DOWNLOAD EBOOKRead and Download eBook Full
Author: W. D. T. Davies
Publisher: John Wiley & Sons
Published: 1970
Total Pages: 404
ISBN-13:
DOWNLOAD EBOOKAuthor: W.D.T. Davies
Publisher:
Published: 1970
Total Pages:
ISBN-13:
DOWNLOAD EBOOKAuthor: W. D. T. Davies
Publisher:
Published: 1970
Total Pages: 380
ISBN-13:
DOWNLOAD EBOOKAuthor: Yiannis Boutalis
Publisher: Springer Science & Business
Published: 2014-04-23
Total Pages: 316
ISBN-13: 3319063642
DOWNLOAD EBOOKPresenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented. Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented. The neurofuzzy model combines concepts from fuzzy systems and recurrent high-order neural networks to produce powerful system approximations that are used for adaptive control. The FCN model stems from fuzzy cognitive maps and uses the notion of “concepts” and their causal relationships to capture the behavior of complex systems. The book shows how, with the benefit of proper training algorithms, these models are potent system emulators suitable for use in engineering systems. All chapters are supported by illustrative simulation experiments, while separate chapters are devoted to the potential industrial applications of each model including projects in: • contemporary power generation; • process control and • conventional benchmarking problems. Researchers and graduate students working in adaptive estimation and intelligent control will find Neurofuzzy Adaptive Control of interest both for the currency of its models and because it demonstrates their relevance for real systems. The monograph also shows industrial engineers how to test intelligent adaptive control easily using proven theoretical results.
Author: Betty H. C. Cheng
Publisher: Springer Science & Business Media
Published: 2009-06-19
Total Pages: 271
ISBN-13: 3642021603
DOWNLOAD EBOOKThe carefully reviewed papers in this state-of-the-art survey describe a wide range of approaches coming from different strands of software engineering, and look forward to future challenges facing this ever-resurgent and exacting field of research.
Author: Danny Weyns
Publisher: John Wiley & Sons
Published: 2020-10-19
Total Pages: 288
ISBN-13: 1119574927
DOWNLOAD EBOOKA concise and practical introduction to the foundations and engineering principles of self-adaptation Though it has recently gained significant momentum, the topic of self-adaptation remains largely under-addressed in academic and technical literature. This book changes that. Using a systematic and holistic approach, An Introduction to Self-adaptive Systems: A Contemporary Software Engineering Perspective provides readers with an accessible set of basic principles, engineering foundations, and applications of self-adaptation in software-intensive systems. It places self-adaptation in the context of techniques like uncertainty management, feedback control, online reasoning, and machine learning while acknowledging the growing consensus in the software engineering community that self-adaptation will be a crucial enabling feature in tackling the challenges of new, emerging, and future systems. The author combines cutting-edge technical research with basic principles and real-world insights to create a practical and strategically effective guide to self-adaptation. He includes features such as: An analysis of the foundational engineering principles and applications of self-adaptation in different domains, including the Internet-of-Things, cloud computing, and cyber-physical systems End-of-chapter exercises at four different levels of complexity and difficulty An accompanying author-hosted website with slides, selected exercises and solutions, models, and code Perfect for researchers, students, teachers, industry leaders, and practitioners in fields that directly or peripherally involve software engineering, as well as those in academia involved in a class on self-adaptivity, this book belongs on the shelves of anyone with an interest in the future of software and its engineering.
Author: Bahram Shafai
Publisher: Springer
Published: 2012-04-30
Total Pages: 500
ISBN-13: 9781461432029
DOWNLOAD EBOOKThis book offers comprehensive coverage of identification and adaptive control while familiarizing graduate students and practicing engineers with computational software tools such as MATLAB and SIMULINK and describing the underlying theoretical concepts. Identification is the process of mathematically modeling a system based on measurement data that may be limited or uncertain. Adaptive control is the means whereby a system that is poorly modeled is controlled adequately. Therefore the topical coverage is divided into two parts: Part I describes fundamental topics of system identification independent of adaptive control and discusses nonparametric and parameteric estimation methods while emphasizing least squares techniques instrumental variables and prediction error methods. Part II describes various methods of adaptive control in which the materials discussed in Part I are essential for control purposes, including model reference, adaptive control and self-tuning regulators.
Author: P. H. Hammond
Publisher: Springer
Published: 2013-11-11
Total Pages: 360
ISBN-13: 1489962891
DOWNLOAD EBOOKAuthor: Rogério de Lemos
Publisher: Springer
Published: 2013-01-03
Total Pages: 402
ISBN-13: 3642358136
DOWNLOAD EBOOKAlthough the self-adaptability of systems has been studied in a wide range of disciplines, from biology to robotics, only recently has the software engineering community recognized its key role in enabling the development of self-adaptive systems that are able to adapt to internal faults, changing requirements, and evolving environments. The 15 carefully reviewed papers included in this state-of-the-art survey were presented at the International Seminar on "Software Engineering for Self-Adaptive Systems", held in Dagstuhl Castle, Germany, in October 2010. Continuing the course of the first book of the series on "Software Engineering for Self-Adaptive Systems" the collection of papers in this second volume comprises a research roadmap accompanied by four elaborating working group papers. Next there are two parts - with three papers each - entitled "Requirements and Policies" and "Design Issues"; part four of the book contains four papers covering a wide range of "Applications".
Author: P. R. Kumar
Publisher: SIAM
Published: 2015-12-15
Total Pages: 371
ISBN-13: 1611974259
DOWNLOAD EBOOKSince its origins in the 1940s, the subject of decision making under uncertainty has grown into a diversified area with application in several branches of engineering and in those areas of the social sciences concerned with policy analysis and prescription. These approaches required a computing capacity too expensive for the time, until the ability to collect and process huge quantities of data engendered an explosion of work in the area. This book provides succinct and rigorous treatment of the foundations of stochastic control; a unified approach to filtering, estimation, prediction, and stochastic and adaptive control; and the conceptual framework necessary to understand current trends in stochastic control, data mining, machine learning, and robotics.