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Identification And Iterative Learning Control For Building Systems A Data Driven Approach
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Book Synopsis Iterative Learning Control by : Zeungnam Bien
Download or read book Iterative Learning Control written by Zeungnam Bien and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Iterative Learning Control (ILC) differs from most existing control methods in the sense that, it exploits every possibility to incorporate past control informa tion, such as tracking errors and control input signals, into the construction of the present control action. There are two phases in Iterative Learning Control: first the long term memory components are used to store past control infor mation, then the stored control information is fused in a certain manner so as to ensure that the system meets control specifications such as convergence, robustness, etc. It is worth pointing out that, those control specifications may not be easily satisfied by other control methods as they require more prior knowledge of the process in the stage of the controller design. ILC requires much less information of the system variations to yield the desired dynamic be haviors. Due to its simplicity and effectiveness, ILC has received considerable attention and applications in many areas for the past one and half decades. Most contributions have been focused on developing new ILC algorithms with property analysis. Since 1992, the research in ILC has progressed by leaps and bounds. On one hand, substantial work has been conducted and reported in the core area of developing and analyzing new ILC algorithms. On the other hand, researchers have realized that integration of ILC with other control techniques may give rise to better controllers that exhibit desired performance which is impossible by any individual approach.
Book Synopsis Model Free Adaptive Control by : Zhongsheng Hou
Download or read book Model Free Adaptive Control written by Zhongsheng Hou and published by CRC Press. This book was released on 2013-09-24 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Free Adaptive Control: Theory and Applications summarizes theory and applications of model-free adaptive control (MFAC). MFAC is a novel adaptive control method for the unknown discrete-time nonlinear systems with time-varying parameters and time-varying structure, and the design and analysis of MFAC merely depend on the measured input and output data of the controlled plant, which makes it more applicable for many practical plants. This book covers new concepts, including pseudo partial derivative, pseudo gradient, pseudo Jacobian matrix, and generalized Lipschitz conditions, etc.; dynamic linearization approaches for nonlinear systems, such as compact-form dynamic linearization, partial-form dynamic linearization, and full-form dynamic linearization; a series of control system design methods, including MFAC prototype, model-free adaptive predictive control, model-free adaptive iterative learning control, and the corresponding stability analysis and typical applications in practice. In addition, some other important issues related to MFAC are also discussed. They are the MFAC for complex connected systems, the modularized controller designs between MFAC and other control methods, the robustness of MFAC, and the symmetric similarity for adaptive control system design. The book is written for researchers who are interested in control theory and control engineering, senior undergraduates and graduated students in engineering and applied sciences, as well as professional engineers in process control.
Book Synopsis Data-Driven Iterative Learning Control for Discrete-Time Systems by : Ronghu Chi
Download or read book Data-Driven Iterative Learning Control for Discrete-Time Systems written by Ronghu Chi and published by Springer Nature. This book was released on 2022-11-15 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book belongs to the subject of control and systems theory. It studies a novel data-driven framework for the design and analysis of iterative learning control (ILC) for nonlinear discrete-time systems. A series of iterative dynamic linearization methods is discussed firstly to build a linear data mapping with respect of the system’s output and input between two consecutive iterations. On this basis, this work presents a series of data-driven ILC (DDILC) approaches with rigorous analysis. After that, this work also conducts significant extensions to the cases with incomplete data information, specified point tracking, higher order law, system constraint, nonrepetitive uncertainty, and event-triggered strategy to facilitate the real applications. The readers can learn the recent progress on DDILC for complex systems in practical applications. This book is intended for academic scholars, engineers, and graduate students who are interested in learning control, adaptive control, nonlinear systems, and related fields.
Book Synopsis Mechanical Engineering And Control Systems - Proceedings Of 2015 International Conference (Mecs2015) by : Xiaolong Li
Download or read book Mechanical Engineering And Control Systems - Proceedings Of 2015 International Conference (Mecs2015) written by Xiaolong Li and published by World Scientific. This book was released on 2016-01-15 with total page 543 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book consists of 113 selected papers presented at the 2015 International Conference on Mechanical Engineering and Control Systems (MECS2015), which was held in Wuhan, China during January 23-25, 2015. All accepted papers have been subjected to strict peer review by two to four expert referees, and selected based on originality, ability to test ideas and contribution to knowledge.MECS2015 focuses on eight main areas, namely, Mechanical Engineering, Automation, Computer Networks, Signal Processing, Pattern Recognition and Artificial Intelligence, Electrical Engineering, Material Engineering, and System Design. The conference provided an opportunity for researchers to exchange ideas and application experiences, and to establish business or research relations, finding global partners for future collaborations. The conference program was extremely rich, profound and featured high-impact presentations of selected papers and additional late-breaking contributions.
Book Synopsis Iterative Identification and Control by : Pedro Albertos
Download or read book Iterative Identification and Control written by Pedro Albertos and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: An exposition of the interplay between the modelling of dynamic systems and the design of feedback controllers based on these models. The authors of individual chapters are some of the most renowned and authoritative figures in the fields of system identification and control design.
Book Synopsis Iterative Identification and Control by : P. Albertos Pérez
Download or read book Iterative Identification and Control written by P. Albertos Pérez and published by Springer Science & Business Media. This book was released on 2002-05-21 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: An exposition of the interplay between the modelling of dynamic systems and the design of feedback controllers based on these models. The authors of individual chapters are some of the most renowned and authoritative figures in the fields of system identification and control design.
Book Synopsis Intelligent Optimization and Control of Complex Metallurgical Processes by : Min Wu
Download or read book Intelligent Optimization and Control of Complex Metallurgical Processes written by Min Wu and published by Springer Nature. This book was released on 2019-11-09 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the intelligent optimization and control of complex metallurgical processes, including intelligent optimization and control of raw-material proportioning processes, coking process, and reheating furnaces; intelligent control of thermal state parameters in sintering processes; and intelligent decoupling control of gas collection and mixing-and-pressurization processes. The intelligent control and optimization methods presented were originally applied to complex metallurgical processes by the authors, and their effectiveness and their advantages have been theoretically proven and demonstrated practically. This book offers an up-to-date overview of this active research area, and provides readers with state-of-the-art methods for the control of complex metallurgical processes.
Download or read book Applied Mechanics Reviews written by and published by . This book was released on 1985 with total page 1052 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Data-Driven Science and Engineering by : Steven L. Brunton
Download or read book Data-Driven Science and Engineering written by Steven L. Brunton and published by Cambridge University Press. This book was released on 2022-05-05 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt: A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
Book Synopsis Learning-Based Control by : Zhong-Ping Jiang
Download or read book Learning-Based Control written by Zhong-Ping Jiang and published by Now Publishers. This book was released on 2020-12-07 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: The recent success of Reinforcement Learning and related methods can be attributed to several key factors. First, it is driven by reward signals obtained through the interaction with the environment. Second, it is closely related to the human learning behavior. Third, it has a solid mathematical foundation. Nonetheless, conventional Reinforcement Learning theory exhibits some shortcomings particularly in a continuous environment or in considering the stability and robustness of the controlled process. In this monograph, the authors build on Reinforcement Learning to present a learning-based approach for controlling dynamical systems from real-time data and review some major developments in this relatively young field. In doing so the authors develop a framework for learning-based control theory that shows how to learn directly suboptimal controllers from input-output data. There are three main challenges on the development of learning-based control. First, there is a need to generalize existing recursive methods. Second, as a fundamental difference between learning-based control and Reinforcement Learning, stability and robustness are important issues that must be addressed for the safety-critical engineering systems such as self-driving cars. Third, data efficiency of Reinforcement Learning algorithms need be addressed for safety-critical engineering systems. This monograph provides the reader with an accessible primer on a new direction in control theory still in its infancy, namely Learning-Based Control Theory, that is closely tied to the literature of safe Reinforcement Learning and Adaptive Dynamic Programming.
Book Synopsis Automatic Tuning of PID Controllers by : Karl J. Åström
Download or read book Automatic Tuning of PID Controllers written by Karl J. Åström and published by . This book was released on 1988 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Proceedings of the Second International Forum on Financial Mathematics and Financial Technology by : Zhiyong Zheng
Download or read book Proceedings of the Second International Forum on Financial Mathematics and Financial Technology written by Zhiyong Zheng and published by Springer Nature. This book was released on 2023-07-25 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book is the documentary of the Second International Forum on Financial Mathematics and Financial Technology, with focus on selected aspects of the current and upcoming trends in FinTech. In detail, the included scientific papers cover financial mathematics and FinTech, presenting the innovative mathematical models and state-of-the-art technologies such as deep learning, with the aim to improve the financial analysis and decision-making and enhance the quality of financial services and risk control. The variety of the papers delivers added value for both scholars and practitioners where they will find perfect integration of elegant mathematical models and up-to-date data mining technologies in financial market analysis. Due to COVID-19, the conference was held virtually on August 13–15, 2021, jointly held by the School of Mathematics of Renmin University of China, the Engineering Research Center of Financial Computing and Digital Engineering of Ministry of Education, the Statistics and Big Data Research Institute of Renmin University of China, the Blockchain Research Institute of Renmin University of China, the Zhongguancun Internet Finance Research Institute, and the Renmin University Press.
Book Synopsis Handbook of Reinforcement Learning and Control by : Kyriakos G. Vamvoudakis
Download or read book Handbook of Reinforcement Learning and Control written by Kyriakos G. Vamvoudakis and published by Springer Nature. This book was released on 2021-06-23 with total page 833 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook presents state-of-the-art research in reinforcement learning, focusing on its applications in the control and game theory of dynamic systems and future directions for related research and technology. The contributions gathered in this book deal with challenges faced when using learning and adaptation methods to solve academic and industrial problems, such as optimization in dynamic environments with single and multiple agents, convergence and performance analysis, and online implementation. They explore means by which these difficulties can be solved, and cover a wide range of related topics including: deep learning; artificial intelligence; applications of game theory; mixed modality learning; and multi-agent reinforcement learning. Practicing engineers and scholars in the field of machine learning, game theory, and autonomous control will find the Handbook of Reinforcement Learning and Control to be thought-provoking, instructive and informative.
Book Synopsis Index to IEEE Publications by : Institute of Electrical and Electronics Engineers
Download or read book Index to IEEE Publications written by Institute of Electrical and Electronics Engineers and published by . This book was released on 1995 with total page 1318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Issues for 1973- cover the entire IEEE technical literature.
Book Synopsis Robust and Fault-Tolerant Control by : Krzysztof Patan
Download or read book Robust and Fault-Tolerant Control written by Krzysztof Patan and published by Springer. This book was released on 2019-03-16 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robust and Fault-Tolerant Control proposes novel automatic control strategies for nonlinear systems developed by means of artificial neural networks and pays special attention to robust and fault-tolerant approaches. The book discusses robustness and fault tolerance in the context of model predictive control, fault accommodation and reconfiguration, and iterative learning control strategies. Expanding on its theoretical deliberations the monograph includes many case studies demonstrating how the proposed approaches work in practice. The most important features of the book include: a comprehensive review of neural network architectures with possible applications in system modelling and control; a concise introduction to robust and fault-tolerant control; step-by-step presentation of the control approaches proposed; an abundance of case studies illustrating the important steps in designing robust and fault-tolerant control; and a large number of figures and tables facilitating the performance analysis of the control approaches described. The material presented in this book will be useful for researchers and engineers who wish to avoid spending excessive time in searching neural-network-based control solutions. It is written for electrical, computer science and automatic control engineers interested in control theory and their applications. This monograph will also interest postgraduate students engaged in self-study of nonlinear robust and fault-tolerant control.
Book Synopsis Sensors Fault Diagnosis Trends and Applications by : Piotr Witczak
Download or read book Sensors Fault Diagnosis Trends and Applications written by Piotr Witczak and published by MDPI. This book was released on 2021-09-01 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fault diagnosis has always been a concern for industry. In general, diagnosis in complex systems requires the acquisition of information from sensors and the processing and extracting of required features for the classification or identification of faults. Therefore, fault diagnosis of sensors is clearly important as faulty information from a sensor may lead to misleading conclusions about the whole system. As engineering systems grow in size and complexity, it becomes more and more important to diagnose faulty behavior before it can lead to total failure. In the light of above issues, this book is dedicated to trends and applications in modern-sensor fault diagnosis.
Book Synopsis Low-Rank Approximation by : Ivan Markovsky
Download or read book Low-Rank Approximation written by Ivan Markovsky and published by Springer. This book was released on 2019-01-10 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive exposition of the theory, algorithms, and applications of structured low-rank approximation. Local optimization methods and effective suboptimal convex relaxations for Toeplitz, Hankel, and Sylvester structured problems are presented. A major part of the text is devoted to application of the theory with a range of applications from systems and control theory to psychometrics being described. Special knowledge of the application fields is not required. The second edition of /Low-Rank Approximation/ is a thoroughly edited and extensively rewritten revision. It contains new chapters and sections that introduce the topics of: • variable projection for structured low-rank approximation;• missing data estimation;• data-driven filtering and control;• stochastic model representation and identification;• identification of polynomial time-invariant systems; and• blind identification with deterministic input model. The book is complemented by a software implementation of the methods presented, which makes the theory directly applicable in practice. In particular, all numerical examples in the book are included in demonstration files and can be reproduced by the reader. This gives hands-on experience with the theory and methods detailed. In addition, exercises and MATLAB^® /Octave examples will assist the reader quickly to assimilate the theory on a chapter-by-chapter basis. “Each chapter is completed with a new section of exercises to which complete solutions are provided.” Low-Rank Approximation (second edition) is a broad survey of the Low-Rank Approximation theory and applications of its field which will be of direct interest to researchers in system identification, control and systems theory, numerical linear algebra and optimization. The supplementary problems and solutions render it suitable for use in teaching graduate courses in those subjects as well.
