Optimal Control Of Impulsive Systems Using Adaptive Critic Based Neural Networks

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Advanced Optimal Control and Applications Involving Critic Intelligence

Author : Ding Wang
Publisher : Springer Nature
ISBN 13 : 9811972915
Total Pages : 283 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Advanced Optimal Control and Applications Involving Critic Intelligence by : Ding Wang

Download or read book Advanced Optimal Control and Applications Involving Critic Intelligence written by Ding Wang and published by Springer Nature. This book was released on 2023-01-21 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book intends to report new optimal control results with critic intelligence for complex discrete-time systems, which covers the novel control theory, advanced control methods, and typical applications for wastewater treatment systems. Therein, combining with artificial intelligence techniques, such as neural networks and reinforcement learning, the novel intelligent critic control theory as well as a series of advanced optimal regulation and trajectory tracking strategies are established for discrete-time nonlinear systems, followed by application verifications to complex wastewater treatment processes. Consequently, developing such kind of critic intelligence approaches is of great significance for nonlinear optimization and wastewater recycling. The book is likely to be of interest to researchers and practitioners as well as graduate students in automation, computer science, and process industry who wish to learn core principles, methods, algorithms, and applications in the field of intelligent optimal control. It is beneficial to promote the development of intelligent optimal control approaches and the construction of high-level intelligent systems.

Adaptive Dynamic Programming: Single and Multiple Controllers

Author : Ruizhuo Song
Publisher : Springer
ISBN 13 : 9811317127
Total Pages : 278 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Adaptive Dynamic Programming: Single and Multiple Controllers by : Ruizhuo Song

Download or read book Adaptive Dynamic Programming: Single and Multiple Controllers written by Ruizhuo Song and published by Springer. This book was released on 2018-12-28 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a class of novel optimal control methods and games schemes based on adaptive dynamic programming techniques. For systems with one control input, the ADP-based optimal control is designed for different objectives, while for systems with multi-players, the optimal control inputs are proposed based on games. In order to verify the effectiveness of the proposed methods, the book analyzes the properties of the adaptive dynamic programming methods, including convergence of the iterative value functions and the stability of the system under the iterative control laws. Further, to substantiate the mathematical analysis, it presents various application examples, which provide reference to real-world practices.

Adaptive Critic Control with Robust Stabilization for Uncertain Nonlinear Systems

Author : Ding Wang
Publisher : Springer
ISBN 13 : 9811312532
Total Pages : 317 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Adaptive Critic Control with Robust Stabilization for Uncertain Nonlinear Systems by : Ding Wang

Download or read book Adaptive Critic Control with Robust Stabilization for Uncertain Nonlinear Systems written by Ding Wang and published by Springer. This book was released on 2018-08-10 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reports on the latest advances in adaptive critic control with robust stabilization for uncertain nonlinear systems. Covering the core theory, novel methods, and a number of typical industrial applications related to the robust adaptive critic control field, it develops a comprehensive framework of robust adaptive strategies, including theoretical analysis, algorithm design, simulation verification, and experimental results. As such, it is of interest to university researchers, graduate students, and engineers in the fields of automation, computer science, and electrical engineering wishing to learn about the fundamental principles, methods, algorithms, and applications in the field of robust adaptive critic control. In addition, it promotes the development of robust adaptive critic control approaches, and the construction of higher-level intelligent systems.

Optimal Event-Triggered Control Using Adaptive Dynamic Programming

Author : Sarangapani Jagannathan
Publisher : CRC Press
ISBN 13 : 1040049168
Total Pages : 348 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Optimal Event-Triggered Control Using Adaptive Dynamic Programming by : Sarangapani Jagannathan

Download or read book Optimal Event-Triggered Control Using Adaptive Dynamic Programming written by Sarangapani Jagannathan and published by CRC Press. This book was released on 2024-06-21 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimal Event-triggered Control using Adaptive Dynamic Programming discusses event triggered controller design which includes optimal control and event sampling design for linear and nonlinear dynamic systems including networked control systems (NCS) when the system dynamics are both known and uncertain. The NCS are a first step to realize cyber-physical systems (CPS) or industry 4.0 vision. The authors apply several powerful modern control techniques to the design of event-triggered controllers and derive event-trigger condition and demonstrate closed-loop stability. Detailed derivations, rigorous stability proofs, computer simulation examples, and downloadable MATLAB® codes are included for each case. The book begins by providing background on linear and nonlinear systems, NCS, networked imperfections, distributed systems, adaptive dynamic programming and optimal control, stability theory, and optimal adaptive event-triggered controller design in continuous-time and discrete-time for linear, nonlinear and distributed systems. It lays the foundation for reinforcement learning-based optimal adaptive controller use for infinite horizons. The text then: Introduces event triggered control of linear and nonlinear systems, describing the design of adaptive controllers for them Presents neural network-based optimal adaptive control and game theoretic formulation of linear and nonlinear systems enclosed by a communication network Addresses the stochastic optimal control of linear and nonlinear NCS by using neuro dynamic programming Explores optimal adaptive design for nonlinear two-player zero-sum games under communication constraints to solve optimal policy and event trigger condition Treats an event-sampled distributed linear and nonlinear systems to minimize transmission of state and control signals within the feedback loop via the communication network Covers several examples along the way and provides applications of event triggered control of robot manipulators, UAV and distributed joint optimal network scheduling and control design for wireless NCS/CPS in order to realize industry 4.0 vision An ideal textbook for senior undergraduate students, graduate students, university researchers, and practicing engineers, Optimal Event Triggered Control Design using Adaptive Dynamic Programming instills a solid understanding of neural network-based optimal controllers under event-sampling and how to build them so as to attain CPS or Industry 4.0 vision.

Reinforcement Learning and Dynamic Programming Using Function Approximators

Author : Lucian Busoniu
Publisher : CRC Press
ISBN 13 : 1439821097
Total Pages : 280 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Reinforcement Learning and Dynamic Programming Using Function Approximators by : Lucian Busoniu

Download or read book Reinforcement Learning and Dynamic Programming Using Function Approximators written by Lucian Busoniu and published by CRC Press. This book was released on 2017-07-28 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: From household appliances to applications in robotics, engineered systems involving complex dynamics can only be as effective as the algorithms that control them. While Dynamic Programming (DP) has provided researchers with a way to optimally solve decision and control problems involving complex dynamic systems, its practical value was limited by algorithms that lacked the capacity to scale up to realistic problems. However, in recent years, dramatic developments in Reinforcement Learning (RL), the model-free counterpart of DP, changed our understanding of what is possible. Those developments led to the creation of reliable methods that can be applied even when a mathematical model of the system is unavailable, allowing researchers to solve challenging control problems in engineering, as well as in a variety of other disciplines, including economics, medicine, and artificial intelligence. Reinforcement Learning and Dynamic Programming Using Function Approximators provides a comprehensive and unparalleled exploration of the field of RL and DP. With a focus on continuous-variable problems, this seminal text details essential developments that have substantially altered the field over the past decade. In its pages, pioneering experts provide a concise introduction to classical RL and DP, followed by an extensive presentation of the state-of-the-art and novel methods in RL and DP with approximation. Combining algorithm development with theoretical guarantees, they elaborate on their work with illustrative examples and insightful comparisons. Three individual chapters are dedicated to representative algorithms from each of the major classes of techniques: value iteration, policy iteration, and policy search. The features and performance of these algorithms are highlighted in extensive experimental studies on a range of control applications. The recent development of applications involving complex systems has led to a surge of interest in RL and DP methods and the subsequent need for a quality resource on the subject. For graduate students and others new to the field, this book offers a thorough introduction to both the basics and emerging methods. And for those researchers and practitioners working in the fields of optimal and adaptive control, machine learning, artificial intelligence, and operations research, this resource offers a combination of practical algorithms, theoretical analysis, and comprehensive examples that they will be able to adapt and apply to their own work. Access the authors' website at www.dcsc.tudelft.nl/rlbook/ for additional material, including computer code used in the studies and information concerning new developments.

Neural Information Processing

Author : Long Cheng
Publisher : Springer
ISBN 13 : 3030042391
Total Pages : 708 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Neural Information Processing by : Long Cheng

Download or read book Neural Information Processing written by Long Cheng and published by Springer. This book was released on 2018-12-03 with total page 708 pages. Available in PDF, EPUB and Kindle. Book excerpt: The seven-volume set of LNCS 11301-11307, constitutes the proceedings of the 25th International Conference on Neural Information Processing, ICONIP 2018, held in Siem Reap, Cambodia, in December 2018. The 401 full papers presented were carefully reviewed and selected from 575 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The 7th and final volume, LNCS 11307, is organized in topical sections on robotics and control; biomedical applications; and hardware.

Self-Learning Optimal Control of Nonlinear Systems

Author : Qinglai Wei
Publisher : Springer
ISBN 13 : 981104080X
Total Pages : 242 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Self-Learning Optimal Control of Nonlinear Systems by : Qinglai Wei

Download or read book Self-Learning Optimal Control of Nonlinear Systems written by Qinglai Wei and published by Springer. This book was released on 2017-06-13 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a class of novel, self-learning, optimal control schemes based on adaptive dynamic programming techniques, which quantitatively obtain the optimal control schemes of the systems. It analyzes the properties identified by the programming methods, including the convergence of the iterative value functions and the stability of the system under iterative control laws, helping to guarantee the effectiveness of the methods developed. When the system model is known, self-learning optimal control is designed on the basis of the system model; when the system model is not known, adaptive dynamic programming is implemented according to the system data, effectively making the performance of the system converge to the optimum. With various real-world examples to complement and substantiate the mathematical analysis, the book is a valuable guide for engineers, researchers, and students in control science and engineering.

Cognitive Systems and Signal Processing

Author : Fuchun Sun
Publisher : Springer
ISBN 13 : 9811052301
Total Pages : 626 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Cognitive Systems and Signal Processing by : Fuchun Sun

Download or read book Cognitive Systems and Signal Processing written by Fuchun Sun and published by Springer. This book was released on 2017-07-07 with total page 626 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Conference on Cognitive Systems and Signal Processing, ICCSIP2016, held in Beijing, China, in December 2016. The 59 revised full papers presented were carefully reviewed and selected from 171 submissions. The papers are organized in topical sections on Control and Decision; Image and Video; Machine Learning; Robotics; Cognitive System; Cognitive Signal Processing.

Control of Complex Systems

Author : Kyriakos Vamvoudakis
Publisher : Butterworth-Heinemann
ISBN 13 : 0128054379
Total Pages : 764 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Control of Complex Systems by : Kyriakos Vamvoudakis

Download or read book Control of Complex Systems written by Kyriakos Vamvoudakis and published by Butterworth-Heinemann. This book was released on 2016-07-27 with total page 764 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the era of cyber-physical systems, the area of control of complex systems has grown to be one of the hardest in terms of algorithmic design techniques and analytical tools. The 23 chapters, written by international specialists in the field, cover a variety of interests within the broader field of learning, adaptation, optimization and networked control. The editors have grouped these into the following 5 sections: "Introduction and Background on Control Theory, "Adaptive Control and Neuroscience, "Adaptive Learning Algorithms, "Cyber-Physical Systems and Cooperative Control, "Applications.The diversity of the research presented gives the reader a unique opportunity to explore a comprehensive overview of a field of great interest to control and system theorists. This book is intended for researchers and control engineers in machine learning, adaptive control, optimization and automatic control systems, including Electrical Engineers, Computer Science Engineers, Mechanical Engineers, Aerospace/Automotive Engineers, and Industrial Engineers. It could be used as a text or reference for advanced courses in complex control systems. • Collection of chapters from several well-known professors and researchers that will showcase their recent work • Presents different state-of-the-art control approaches and theory for complex systems • Gives algorithms that take into consideration the presence of modelling uncertainties, the unavailability of the model, the possibility of cooperative/non-cooperative goals and malicious attacks compromising the security of networked teams • Real system examples and figures throughout, make ideas concrete - Includes chapters from several well-known professors and researchers that showcases their recent work - Presents different state-of-the-art control approaches and theory for complex systems - Explores the presence of modelling uncertainties, the unavailability of the model, the possibility of cooperative/non-cooperative goals, and malicious attacks compromising the security of networked teams - Serves as a helpful reference for researchers and control engineers working with machine learning, adaptive control, and automatic control systems

Advances in Reinforcement Learning

Author : Abdelhamid Mellouk
Publisher : BoD – Books on Demand
ISBN 13 : 9533073691
Total Pages : 486 pages
Book Rating : 4.5/5 (33 download)

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Book Synopsis Advances in Reinforcement Learning by : Abdelhamid Mellouk

Download or read book Advances in Reinforcement Learning written by Abdelhamid Mellouk and published by BoD – Books on Demand. This book was released on 2011-01-14 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reinforcement Learning (RL) is a very dynamic area in terms of theory and application. This book brings together many different aspects of the current research on several fields associated to RL which has been growing rapidly, producing a wide variety of learning algorithms for different applications. Based on 24 Chapters, it covers a very broad variety of topics in RL and their application in autonomous systems. A set of chapters in this book provide a general overview of RL while other chapters focus mostly on the applications of RL paradigms: Game Theory, Multi-Agent Theory, Robotic, Networking Technologies, Vehicular Navigation, Medicine and Industrial Logistic.

Adaptive Control Tutorial

Author : Petros Ioannou
Publisher : SIAM
ISBN 13 : 0898716152
Total Pages : 401 pages
Book Rating : 4.8/5 (987 download)

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Book Synopsis Adaptive Control Tutorial by : Petros Ioannou

Download or read book Adaptive Control Tutorial written by Petros Ioannou and published by SIAM. This book was released on 2006-01-01 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed to meet the needs of a wide audience without sacrificing mathematical depth and rigor, Adaptive Control Tutorial presents the design, analysis, and application of a wide variety of algorithms that can be used to manage dynamical systems with unknown parameters. Its tutorial-style presentation of the fundamental techniques and algorithms in adaptive control make it suitable as a textbook. Adaptive Control Tutorial is designed to serve the needs of three distinct groups of readers: engineers and students interested in learning how to design, simulate, and implement parameter estimators and adaptive control schemes without having to fully understand the analytical and technical proofs; graduate students who, in addition to attaining the aforementioned objectives, also want to understand the analysis of simple schemes and get an idea of the steps involved in more complex proofs; and advanced students and researchers who want to study and understand the details of long and technical proofs with an eye toward pursuing research in adaptive control or related topics. The authors achieve these multiple objectives by enriching the book with examples demonstrating the design procedures and basic analysis steps and by detailing their proofs in both an appendix and electronically available supplementary material; online examples are also available. A solution manual for instructors can be obtained by contacting SIAM or the authors. Preface; Acknowledgements; List of Acronyms; Chapter 1: Introduction; Chapter 2: Parametric Models; Chapter 3: Parameter Identification: Continuous Time; Chapter 4: Parameter Identification: Discrete Time; Chapter 5: Continuous-Time Model Reference Adaptive Control; Chapter 6: Continuous-Time Adaptive Pole Placement Control; Chapter 7: Adaptive Control for Discrete-Time Systems; Chapter 8: Adaptive Control of Nonlinear Systems; Appendix; Bibliography; Index

Advances in Neural Networks -- ISNN 2011

Author : Derong Liu
Publisher : Springer
ISBN 13 : 3642211054
Total Pages : 667 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Advances in Neural Networks -- ISNN 2011 by : Derong Liu

Download or read book Advances in Neural Networks -- ISNN 2011 written by Derong Liu and published by Springer. This book was released on 2011-05-20 with total page 667 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 6675, 6676 and 6677 constitutes the refereed proceedings of the 8th International Symposium on Neural Networks, ISNN 2011, held in Guilin, China, in May/June 2011. The total of 215 papers presented in all three volumes were carefully reviewed and selected from 651 submissions. The contributions are structured in topical sections on computational neuroscience and cognitive science; neurodynamics and complex systems; stability and convergence analysis; neural network models; supervised learning and unsupervised learning; kernel methods and support vector machines; mixture models and clustering; visual perception and pattern recognition; motion, tracking and object recognition; natural scene analysis and speech recognition; neuromorphic hardware, fuzzy neural networks and robotics; multi-agent systems and adaptive dynamic programming; reinforcement learning and decision making; action and motor control; adaptive and hybrid intelligent systems; neuroinformatics and bioinformatics; information retrieval; data mining and knowledge discovery; and natural language processing.

Intelligent Autonomous Control of Spacecraft with Multiple Constraints

Author : Qinglei Hu
Publisher : Springer Nature
ISBN 13 : 9819906814
Total Pages : 346 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Intelligent Autonomous Control of Spacecraft with Multiple Constraints by : Qinglei Hu

Download or read book Intelligent Autonomous Control of Spacecraft with Multiple Constraints written by Qinglei Hu and published by Springer Nature. This book was released on 2023-05-02 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the intelligent autonomous control problems for spacecraft with multiple constraints, such as pointing/path constraints, linear/angular velocity constraints, performance constraints, etc. It provides an almost self-contained presentation of dynamics modeling, controller design and analysis, as well as simulation studies. The book aims to offer a valuable guide for researchers and aerospace engineers to address the theoretical and technical difficulties in different applications, ranging from spacecraft attitude reorientation and tracking to spacecraft proximity operations, and is mainly intended for technical and engineering staff engaged in spacecraft dyanmics and control areas.

Neural Information Processing

Author : Biao Luo
Publisher : Springer Nature
ISBN 13 : 9819980828
Total Pages : 607 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Neural Information Processing by : Biao Luo

Download or read book Neural Information Processing written by Biao Luo and published by Springer Nature. This book was released on 2023-11-14 with total page 607 pages. Available in PDF, EPUB and Kindle. Book excerpt: The six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields.

Robust Adaptive Dynamic Programming

Author : Yu Jiang
Publisher : John Wiley & Sons
ISBN 13 : 1119132657
Total Pages : 220 pages
Book Rating : 4.1/5 (191 download)

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Book Synopsis Robust Adaptive Dynamic Programming by : Yu Jiang

Download or read book Robust Adaptive Dynamic Programming written by Yu Jiang and published by John Wiley & Sons. This book was released on 2017-04-13 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive look at state-of-the-art ADP theory and real-world applications This book fills a gap in the literature by providing a theoretical framework for integrating techniques from adaptive dynamic programming (ADP) and modern nonlinear control to address data-driven optimal control design challenges arising from both parametric and dynamic uncertainties. Traditional model-based approaches leave much to be desired when addressing the challenges posed by the ever-increasing complexity of real-world engineering systems. An alternative which has received much interest in recent years are biologically-inspired approaches, primarily RADP. Despite their growing popularity worldwide, until now books on ADP have focused nearly exclusively on analysis and design, with scant consideration given to how it can be applied to address robustness issues, a new challenge arising from dynamic uncertainties encountered in common engineering problems. Robust Adaptive Dynamic Programming zeros in on the practical concerns of engineers. The authors develop RADP theory from linear systems to partially-linear, large-scale, and completely nonlinear systems. They provide in-depth coverage of state-of-the-art applications in power systems, supplemented with numerous real-world examples implemented in MATLAB. They also explore fascinating reverse engineering topics, such how ADP theory can be applied to the study of the human brain and cognition. In addition, the book: Covers the latest developments in RADP theory and applications for solving a range of systems’ complexity problems Explores multiple real-world implementations in power systems with illustrative examples backed up by reusable MATLAB code and Simulink block sets Provides an overview of nonlinear control, machine learning, and dynamic control Features discussions of novel applications for RADP theory, including an entire chapter on how it can be used as a computational mechanism of human movement control Robust Adaptive Dynamic Programming is both a valuable working resource and an intriguing exploration of contemporary ADP theory and applications for practicing engineers and advanced students in systems theory, control engineering, computer science, and applied mathematics.

Adaptive Dynamic Programming

Author : Jiayue Sun
Publisher : Springer Nature
ISBN 13 : 9819959292
Total Pages : 144 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Adaptive Dynamic Programming by : Jiayue Sun

Download or read book Adaptive Dynamic Programming written by Jiayue Sun and published by Springer Nature. This book was released on 2023-10-14 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book focuses on the practical application of Adaptive Dynamic Programming (ADP) in chemotherapy drug delivery, taking into account clinical variables and real-time data. ADP's ability to adapt to changing conditions and make optimal decisions in complex and uncertain situations makes it a valuable tool in addressing pressing challenges in healthcare and other fields. As optimization technology evolves, we can expect to see even more sophisticated and powerful solutions emerge.

Innovative Techniques and Applications of Modelling, Identification and Control

Author : Quanmin Zhu
Publisher : Springer
ISBN 13 : 9811072124
Total Pages : 455 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Innovative Techniques and Applications of Modelling, Identification and Control by : Quanmin Zhu

Download or read book Innovative Techniques and Applications of Modelling, Identification and Control written by Quanmin Zhu and published by Springer. This book was released on 2018-04-20 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the most important findings from the 9th International Conference on Modelling, Identification and Control (ICMIC’17), held in Kunming, China on July 10–12, 2017. It covers most aspects of modelling, identification, instrumentation, signal processing and control, with a particular focus on the applications of research in multi-agent systems, robotic systems, autonomous systems, complex systems, and renewable energy systems. The book gathers thirty comprehensively reviewed and extended contributions, which help to promote evolutionary computation, artificial intelligence, computation intelligence and soft computing techniques to enhance the safety, flexibility and efficiency of engineering systems. Taken together, they offer an ideal reference guide for researchers and engineers in the fields of electrical/electronic engineering, mechanical engineering and communication engineering.