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Iterative Learning Control For Systems With Iteration Varying Trial Lengths


Iterative Learning Control For Systems With Iteration Varying Trial Lengths
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Iterative Learning Control For Systems With Iteration Varying Trial Lengths


Iterative Learning Control For Systems With Iteration Varying Trial Lengths
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Author : Dong Shen
language : en
Publisher: Springer
Release Date : 2019-01-29

Iterative Learning Control For Systems With Iteration Varying Trial Lengths written by Dong Shen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-29 with Technology & Engineering categories.


This book presents a comprehensive and detailed study on iterative learning control (ILC) for systems with iteration-varying trial lengths. Instead of traditional ILC, which requires systems to repeat on a fixed time interval, this book focuses on a more practical case where the trial length might randomly vary from iteration to iteration. The iteration-varying trial lengths may be different from the desired trial length, which can cause redundancy or dropouts of control information in ILC, making ILC design a challenging problem. The book focuses on the synthesis and analysis of ILC for both linear and nonlinear systems with iteration-varying trial lengths, and proposes various novel techniques to deal with the precise tracking problem under non-repeatable trial lengths, such as moving window, switching system, and searching-based moving average operator. It not only discusses recent advances in ILC for systems with iteration-varying trial lengths, but also includes numerousintuitive figures to allow readers to develop an in-depth understanding of the intrinsic relationship between the incomplete information environment and the essential tracking performance. This book is intended for academic scholars and engineers who are interested in learning about control, data-driven control, networked control systems, and related fields. It is also a useful resource for graduate students in the above field.



Iterative Learning Control With Passive Incomplete Information


Iterative Learning Control With Passive Incomplete Information
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Author : Dong Shen
language : en
Publisher: Springer
Release Date : 2018-04-16

Iterative Learning Control With Passive Incomplete Information written by Dong Shen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-16 with Technology & Engineering categories.


This book presents an in-depth discussion of iterative learning control (ILC) with passive incomplete information, highlighting the incomplete input and output data resulting from practical factors such as data dropout, transmission disorder, communication delay, etc.—a cutting-edge topic in connection with the practical applications of ILC. It describes in detail three data dropout models: the random sequence model, Bernoulli variable model, and Markov chain model—for both linear and nonlinear stochastic systems. Further, it proposes and analyzes two major compensation algorithms for the incomplete data, namely, the intermittent update algorithm and successive update algorithm. Incomplete information environments include random data dropout, random communication delay, random iteration-varying lengths, and other communication constraints. With numerous intuitive figures to make the content more accessible, the book explores several potential solutions to this topic, ensuring that readers are not only introduced to the latest advances in ILC for systems with random factors, but also gain an in-depth understanding of the intrinsic relationship between incomplete information environments and essential tracking performance. It is a valuable resource for academics and engineers, as well as graduate students who are interested in learning about control, data-driven control, networked control systems, and related fields.



Predictive Learning Control For Unknown Nonaffine Nonlinear Systems


Predictive Learning Control For Unknown Nonaffine Nonlinear Systems
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Author : Qiongxia Yu
language : en
Publisher: Springer Nature
Release Date : 2023-02-17

Predictive Learning Control For Unknown Nonaffine Nonlinear Systems written by Qiongxia Yu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-17 with Technology & Engineering categories.


This book investigates both theory and various applications of predictive learning control (PLC) which is an advanced technology for complex nonlinear systems. To avoid the difficult modeling problem for complex nonlinear systems, this book begins with the design and theoretical analysis of PLC method without using mechanism model information of the system, and then a series of PLC methods is designed that can cope with system constraints, varying trial lengths, unknown time delay, and available and unavailable system states sequentially. Applications of the PLC on both railway and urban road transportation systems are also studied. The book is intended for researchers, engineers, and graduate students who are interested in predictive control, learning control, intelligent transportation systems and related fields.



Discrete Time Adaptive Iterative Learning Control


Discrete Time Adaptive Iterative Learning Control
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Author : Ronghu Chi
language : en
Publisher: Springer Nature
Release Date : 2022-03-21

Discrete Time Adaptive Iterative Learning Control written by Ronghu Chi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-21 with Technology & Engineering categories.


This book belongs to the subject of control and systems theory. The discrete-time adaptive iterative learning control (DAILC) is discussed as a cutting-edge of ILC and can address random initial states, iteration-varying targets, and other non-repetitive uncertainties in practical applications. This book begins with the design and analysis of model-based DAILC methods by referencing the tools used in the discrete-time adaptive control theory. To overcome the extreme difficulties in modeling a complex system, the data-driven DAILC methods are further discussed by building a linear parametric data mapping between two consecutive iterations. Other significant improvements and extensions of the model-based/data-driven DAILC are also studied to facilitate broader applications. The readers can learn the recent progress on DAILC with consideration of various 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.



Data Driven Iterative Learning Control For Discrete Time Systems


Data Driven Iterative Learning Control For Discrete Time Systems
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Author : Ronghu Chi
language : en
Publisher: Springer Nature
Release Date : 2022-11-15

Data Driven Iterative Learning Control For Discrete Time Systems written by Ronghu Chi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-15 with Technology & Engineering categories.


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.



Variable Gain Design In Stochastic Iterative Learning Control


Variable Gain Design In Stochastic Iterative Learning Control
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Author : Dong Shen
language : en
Publisher: Springer Nature
Release Date : 2025-01-02

Variable Gain Design In Stochastic Iterative Learning Control written by Dong Shen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-02 with Technology & Engineering categories.


This book investigates the critical gain design in stochastic iterative learning control (SILC), including four specific gain design strategies: decreasing gain design, adaptive gain design, event-triggering gain design, and optimal gain design. The key concept for the gain design is to balance multiple performance indices such as high tracking precision, effective noise reduction, and fast convergence speed. These gain design techniques can be applied to various control algorithms for stochastic systems to realize a high tracking performance. This book provides a series of design and analysis techniques for the establishment of a systematic framework of gain design in SILC. The book is intended for scholars and graduate students who are interested in stochastic control, recursive algorithms design, and iterative learning control.



Iterative Learning Control For Network Systems Under Constrained Information Communication


Iterative Learning Control For Network Systems Under Constrained Information Communication
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Author : Wenjun Xiong
language : en
Publisher: Springer Nature
Release Date : 2024-03-26

Iterative Learning Control For Network Systems Under Constrained Information Communication written by Wenjun Xiong and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-26 with Technology & Engineering categories.


This book focuses on the subject area of Network Systems and Control Theory, providing a comprehensive examination of the dynamic behavior of networked systems operating under communication constraints. It introduces innovative iterative learning control strategies that aim to ensure stability, consistency, and security of networked systems. The field of networked systems has garnered significant interest from scientists and engineers across various disciplines, including information, electrical, transportation, life, social, and management sciences. This book consistently addresses a wide range of issues related to networked systems, emphasizing the critical impact of communication constraints on stability and security. It highlights the effectiveness and importance of iterative learning methods in tackling these challenges. Suitable for both undergraduate and graduate students interested in networked systems and iterative learning control, this book alsoserves as a valuable resource for university faculty and engineers engaged in complex systems, control theory research, and real-world applications. Its broad appeal extends to professionals working in related fields, seeking a deeper understanding of networked systems and their control mechanisms.



Security And Privacy In New Computing Environments


Security And Privacy In New Computing Environments
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Author : Jun Cai
language : en
Publisher: Springer Nature
Release Date : 2024-12-31

Security And Privacy In New Computing Environments written by Jun Cai and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-31 with Computers categories.


This book constitutes the refereed proceedings of the 6th International Conference on Security and Privacy in New Computing Environments, SPNCE 2023, held in Guangzhou, China, during November 25-26, 2023. The 29 full papers were selected from 75 submissions and are grouped in these thematical parts: IoT, network security and privacy challenges; multi-party privacy preserving neural networks; security and privacy steganography and forensics.



Advances In Engineering Research And Application


Advances In Engineering Research And Application
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Author : Kai-Uwe Sattler
language : en
Publisher: Springer Nature
Release Date : 2020-11-23

Advances In Engineering Research And Application written by Kai-Uwe Sattler and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-23 with Technology & Engineering categories.


This proceedings book features volumes gathered selected contributions from the International Conference on Engineering Research and Applications (ICERA 2020) organized at Thai Nguyen University of Technology on December 1–2, 2020. The conference focused on the original researches in a broad range of areas, such as Mechanical Engineering, Materials and Mechanics of Materials, Mechatronics and Micromechatronics, Automotive Engineering, Electrical and Electronics Engineering, and Information and Communication Technology. Therefore, the book provides the research community with authoritative reports on developments in the most exciting areas in these fields.



Proceedings Of 2020 Chinese Intelligent Systems Conference


Proceedings Of 2020 Chinese Intelligent Systems Conference
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Author : Yingmin Jia
language : en
Publisher: Springer Nature
Release Date : 2020-09-23

Proceedings Of 2020 Chinese Intelligent Systems Conference written by Yingmin Jia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-23 with Technology & Engineering categories.


The book focuses on new theoretical results and techniques in the field of intelligent systems and control. It provides in-depth studies on a number of major topics such as Multi-Agent Systems, Complex Networks, Intelligent Robots, Complex System Theory and Swarm Behavior, Event-Triggered Control and Data-Driven Control, Robust and Adaptive Control, Big Data and Brain Science, Process Control, Intelligent Sensor and Detection Technology, Deep learning and Learning Control Guidance, Navigation and Control of Flight Vehicles and so on. Given its scope, the book will benefit all researchers, engineers, and graduate students who want to learn about cutting-edge advances in intelligent systems, intelligent control, and artificial intelligence.