System Identification for Self-adaptive Control

System Identification for Self-adaptive Control PDF Author: W. D. T. Davies
Publisher: John Wiley & Sons
ISBN:
Category : Adaptive control systems
Languages : en
Pages : 404

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Book Description

System Identification for Self-adaptive Control

System Identification for Self-adaptive Control PDF Author: W. D. T. Davies
Publisher: John Wiley & Sons
ISBN:
Category : Adaptive control systems
Languages : en
Pages : 404

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Book Description


System Identification for Self-Adaptive

System Identification for Self-Adaptive PDF Author: W.D.T. Davies
Publisher:
ISBN:
Category : Adaptive control systems
Languages : en
Pages :

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System Identification and Adaptive Control

System Identification and Adaptive Control PDF Author: Yiannis Boutalis
Publisher: Springer Science & Business
ISBN: 3319063642
Category : Technology & Engineering
Languages : en
Pages : 313

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Book Description
Presenting 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.

Software Engineering for Self-Adaptive Systems

Software Engineering for Self-Adaptive Systems PDF Author: Betty H. C. Cheng
Publisher: Springer Science & Business Media
ISBN: 3642021603
Category : Computers
Languages : en
Pages : 271

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Book Description
The 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.

Software Engineering for Self-Adaptive Systems

Software Engineering for Self-Adaptive Systems PDF Author: Betty H. C. Cheng
Publisher: Springer
ISBN: 3642021611
Category : Computers
Languages : en
Pages : 261

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Book Description
Although 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 future software systems that are able to self-adapt to changes that may occur in the system, its requirements, or the environment in which it is deployed. The 12 carefully reviewed papers included in this state-of-the-art survey originate from the International Seminar on Software Engineering for Self-Adaptive Systems, held in Dagstuhl Castle, Germany, in January 2008. They examine the current state-of-the-art in the field, describing a wide range of approaches coming from different strands of software engineering, and present future challenges facing this ever-resurgent and challenging field of research. Also included in this book is an invited roadmap paper on the research challenges facing self-adaptive systems within the area of software engineering, based on discussions at the Dagstuhl Seminar and put together by several of its participants. The papers have been divided into topical sections on architecture-based self-adaptation, context-aware and model-driven self-adaptation, and self-healing. These are preceded by three research roadmap papers.

Theory of Self-Adaptive Control Systems

Theory of Self-Adaptive Control Systems PDF Author: P. H. Hammond
Publisher: Springer
ISBN: 1489962891
Category : Technology & Engineering
Languages : en
Pages : 360

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Software Engineering for Self-Adaptive Systems

Software Engineering for Self-Adaptive Systems PDF Author: Rogério de Lemos
Publisher: Springer
ISBN: 3642358136
Category : Computers
Languages : en
Pages : 393

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Book Description
Although 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".

Software Engineering for Self-Adaptive Systems III. Assurances

Software Engineering for Self-Adaptive Systems III. Assurances PDF Author: Rogério de Lemos
Publisher: Springer
ISBN: 3319741837
Category : Computers
Languages : en
Pages : 435

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Book Description
A major challenge for modern software systems is to become more cost-effective, while being versatile, flexible, resilient, energy-efficient, customizable, and configurable when reacting to run-time changes that may occur within the system itself, its environment or requirements. One of the most promising approaches to achieving such properties is to equip the software system with self-adaptation capabilities. Despite recent advances in this area, one key aspect that remains to be tackled in depth is the provision of assurances. Originating from a Dagstuhl seminar held in December 2013, this book constitutes the third volume in the series “Software Engineering for Self-Adaptive Systems”, and looks specifically into the provision of assurances. Opening with an overview chapter on Research Challenges, the book presents 13 further chapters written and carefully reviewed by internationally leading researchers in the field. The book is divided into topical sections on research challenges, evaluation, integration and coordination, and reference architectures and platforms.

An Introduction to Self-adaptive Systems

An Introduction to Self-adaptive Systems PDF Author: Danny Weyns
Publisher: John Wiley & Sons
ISBN: 1119574943
Category : Technology & Engineering
Languages : en
Pages : 288

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Book Description
A 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.

Stochastic Systems

Stochastic Systems PDF Author: P. R. Kumar
Publisher: SIAM
ISBN: 1611974259
Category : Mathematics
Languages : en
Pages : 371

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Book Description
Since 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.