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Author: Max Cohen
Publisher: Springer Nature
ISBN: 303129310X
Category : Technology & Engineering
Languages : en
Pages : 209
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Book Description
This book stems from the growing use of learning-based techniques, such as reinforcement learning and adaptive control, in the control of autonomous and safety-critical systems. Safety is critical to many applications, such as autonomous driving, air traffic control, and robotics. As these learning-enabled technologies become more prevalent in the control of autonomous systems, it becomes increasingly important to ensure that such systems are safe. To address these challenges, the authors provide a self-contained treatment of learning-based control techniques with rigorous guarantees of stability and safety. This book contains recent results on provably correct control techniques from specifications that go beyond safety and stability, such as temporal logic formulas. The authors bring together control theory, optimization, machine learning, and formal methods and present worked-out examples and extensive simulation examples to complement the mathematical style of presentation. Prerequisites are minimal, and the underlying ideas are accessible to readers with only a brief background in control-theoretic ideas, such as Lyapunov stability theory.
Author: Max Cohen
Publisher: Springer Nature
ISBN: 303129310X
Category : Technology & Engineering
Languages : en
Pages : 209
Get Book Here
Book Description
This book stems from the growing use of learning-based techniques, such as reinforcement learning and adaptive control, in the control of autonomous and safety-critical systems. Safety is critical to many applications, such as autonomous driving, air traffic control, and robotics. As these learning-enabled technologies become more prevalent in the control of autonomous systems, it becomes increasingly important to ensure that such systems are safe. To address these challenges, the authors provide a self-contained treatment of learning-based control techniques with rigorous guarantees of stability and safety. This book contains recent results on provably correct control techniques from specifications that go beyond safety and stability, such as temporal logic formulas. The authors bring together control theory, optimization, machine learning, and formal methods and present worked-out examples and extensive simulation examples to complement the mathematical style of presentation. Prerequisites are minimal, and the underlying ideas are accessible to readers with only a brief background in control-theoretic ideas, such as Lyapunov stability theory.
Author: Zhong-Ping Jiang
Publisher: Now Publishers
ISBN: 9781680837520
Category : Technology & Engineering
Languages : en
Pages : 122
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Book Description
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.
Author: Naira Hovakimyan
Publisher: SIAM
ISBN: 0898717043
Category : Science
Languages : en
Pages : 333
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Book Description
Contains results not yet published in technical journals and conference proceedings.
Author: Wei Xiao
Publisher: Springer Nature
ISBN: 3031275764
Category : Technology & Engineering
Languages : en
Pages : 228
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Book Description
This book presents the concept of Control Barrier Function (CBF), which captures the evolution of safety requirements during the execution of a system and can be used to enforce safety. Safety is formalized using an emerging state-of-the-art approach based on CBFs, and many illustrative examples from autonomous driving, traffic control, and robot control are provided. Safety is central to autonomous systems since they are intended to operate with minimal or no human supervision, and a single failure could result in catastrophic results. The authors discuss how safety can be guaranteed via both theoretical and application perspectives. This presented method is computationally efficient and can be easily implemented in real-time systems that require high-frequency reactive control. In addition, the CBF approach can easily deal with nonlinear models and complex constraints used in a wide spectrum of applications, including autonomous driving, robotics, and traffic control. With the proliferation of autonomous systems, such as self-driving cars, mobile robots, and unmanned air vehicles, safety plays a crucial role in ensuring their widespread adoption. This book considers the integration of safety guarantees into the operation of such systems including typical safety requirements that involve collision avoidance, technological system limitations, and bounds on real-time executions. Adaptive approaches for safety are also proposed for time-varying execution bounds and noisy dynamics.
Author: Jesus Hamilton Ortiz
Publisher: BoD – Books on Demand
ISBN: 1839687398
Category : Technology & Engineering
Languages : en
Pages : 184
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Book Description
Collaborative and Humanoid Robots guides readers through the fundamentals and state-of-the-art concepts and future expectations of robotics. It showcases interesting research topics on robots and cobots by researchers, industry practitioners, and academics. Divided into two sections on “Collaborative Robots” and “Humanoid Robots,” this book includes surveys of recent publications that investigative the interaction between humanoid robots and humans; safe adaptive trajectory tracking control of robots; 3D printed, self-learning robots; robot trajectory, guidance, and control; social robots; Tiny Blind assistive humanoid robots; and more.
Author: W. Eric Wong
Publisher: World Scientific
ISBN: 9814340928
Category : Computers
Languages : en
Pages : 308
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Book Description
This book focuses on the topic of improving software quality using adaptive control approaches. As software systems grow in complexity, some of the central challenges include their ability to self-manage and adapt at run time, responding to changing user needs and environments, faults, and vulnerabilities. Control theory approaches presented in the book provide some of the answers to these challenges. The book weaves together diverse research topics (such as requirements engineering, software development processes, pervasive and autonomic computing, service-oriented architectures, on-line adaptation of software behavior, testing and QoS control) into a coherent whole. Written by world-renowned experts, this book is truly a noteworthy and authoritative reference for students, researchers and practitioners to better understand how the adaptive control approach can be applied to improve the quality of software systems. Book chapters also outline future theoretical and experimental challenges for researchers in this area.
Author: Massih-Reza Amini
Publisher: Springer Nature
ISBN: 3031264126
Category : Computers
Languages : en
Pages : 680
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Book Description
The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022. The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions. The volumes are organized in topical sections as follows: Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge graphs; social network analysis; graph neural networks; natural language processing and text mining; conversational systems; Part III: Deep learning; robust and adversarial machine learning; generative models; computer vision; meta-learning, neural architecture search; Part IV: Reinforcement learning; multi-agent reinforcement learning; bandits and online learning; active and semi-supervised learning; private and federated learning; Part V: Supervised learning; probabilistic inference; optimal transport; optimization; quantum, hardware; sustainability; Part VI: Time series; financial machine learning; applications; applications: transportation; demo track.
Author:
Publisher: Elsevier
ISBN: 0443297754
Category : Technology & Engineering
Languages : en
Pages : 550
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Book Description
Method of Process Systems in Energy Systems: Current System Part 1, Volume Eight, the latest release in the Methods in Chemical Process Safety series, highlights new advances in the field, with this new volume presenting interesting chapters written by an international board of authors. - Provides the authority and expertise of leading contributors from an international board of authors - Presents the latest release in the Methods in Chemical Process Safety series - Includes the authority and expertise of leading contributors from an international board of authors
Author: Yingmin Jia
Publisher: Springer Nature
ISBN: 9811663289
Category : Technology & Engineering
Languages : en
Pages : 909
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Book Description
This book presents the proceedings of the 17th Chinese Intelligent Systems Conference, held in Fuzhou, China, on Oct 16-17, 2021. It focuses on new theoretical results and techniques in the field of intelligent systems and control. This is achieved by providing in-depth study 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. The book is particularly suited for readers who are interested in learning intelligent system and control and artificial intelligence. The book can benefit researchers, engineers, and graduate students.
Author: Nicholas Roy
Publisher: MIT Press
ISBN: 0262315734
Category : Technology & Engineering
Languages : en
Pages : 501
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Book Description
Papers from a flagship conference reflect the latest developments in the field, including work in such rapidly advancing areas as human-robot interaction and formal methods. Robotics: Science and Systems VIII spans a wide spectrum of robotics, bringing together contributions from researchers working on the mathematical foundations of robotics, robotics applications, and analysis of robotics systems. This volume presents the proceedings of the eighth annual Robotics: Science and Systems (RSS) conference, held in July 2012 at the University of Sydney. The contributions reflect the exciting diversity of the field, presenting the best, the newest, and the most challenging work on such topics as mechanisms, kinematics, dynamics and control, human-robot interaction and human-centered systems, distributed systems, mobile systems and mobility, manipulation, field robotics, medical robotics, biological robotics, robot perception, and estimation and learning in robotic systems. The conference and its proceedings reflect not only the tremendous growth of robotics as a discipline but also the desire in the robotics community for a flagship event at which the best of the research in the field can be presented.
