Learning Control

Book Learning Control Cover

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  • Publisher : Elsevier
  • Release : 05 December 2020
  • ISBN : 9780128223154
  • Page : 280 pages
  • Rating : 4.5/5 from 103 voters

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Learning Control: Applications in Robotics and Complex Dynamical Systems provides a foundational understanding of control theory while also introducing exciting cutting-edge technologies in the field of learning-based control. State-of-the-art techniques involving machine learning and artificial intelligence (AI) are covered, as are foundational control theories and more established techniques such as adaptive learning control, reinforcement learning control, impedance control, and deep reinforcement control. Each chapter includes case studies and real-world applications in robotics, AI, aircraft and other vehicles and complex dynamical systems. Computational methods for control systems, particularly those used for developing AI and other machine learning techniques, are also discussed at length. Provides foundational control theory concepts, along with advanced techniques and the latest advances in adaptive control and robotics Introduces state-of-the-art learning-based control technologies and their applications in robotics and other complex dynamical systems Demonstrates computational techniques for control systems Covers iterative learning impedance control in both human-robot interaction and collaborative robots

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Learning Control

Learning Control
  • Author : Dan Zhang,Bin Wei
  • Publisher : Elsevier
  • Release Date : 2020-12-05
  • ISBN : 9780128223154
GET THIS BOOKLearning Control

Learning Control: Applications in Robotics and Complex Dynamical Systems provides a foundational understanding of control theory while also introducing exciting cutting-edge technologies in the field of learning-based control. State-of-the-art techniques involving machine learning and artificial intelligence (AI) are covered, as are foundational control theories and more established techniques such as adaptive learning control, reinforcement learning control, impedance control, and deep reinforcement control. Each chapter includes case studies and real-world applications in robotics, AI, aircraft and other vehicles and complex dynamical

Iterative Learning Control

Iterative Learning Control
  • Author : David H. Owens
  • Publisher : Springer
  • Release Date : 2015-10-31
  • ISBN : 9781447167723
GET THIS BOOKIterative Learning Control

This book develops a coherent and quite general theoretical approach to algorithm design for iterative learning control based on the use of operator representations and quadratic optimization concepts including the related ideas of inverse model control and gradient-based design. Using detailed examples taken from linear, discrete and continuous-time systems, the author gives the reader access to theories based on either signal or parameter optimization. Although the two approaches are shown to be related in a formal mathematical sense, the text

Iterative Learning Control

Iterative Learning Control
  • Author : Zeungnam Bien,Jian-Xin Xu
  • Publisher : Springer Science & Business Media
  • Release Date : 2012-12-06
  • ISBN : 9781461556299
GET THIS BOOKIterative Learning Control

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

Iterative Learning Control for Multi-agent Systems Coordination

Iterative Learning Control for Multi-agent Systems Coordination
  • Author : Shiping Yang,Jian-Xin Xu,Xuefang Li,Dong Shen
  • Publisher : John Wiley & Sons
  • Release Date : 2017-03-03
  • ISBN : 9781119189060
GET THIS BOOKIterative Learning Control for Multi-agent Systems Coordination

A timely guide using iterative learning control (ILC) as a solution for multi-agent systems (MAS) challenges, showcasing recent advances and industrially relevant applications Explores the synergy between the important topics of iterative learning control (ILC) and multi-agent systems (MAS) Concisely summarizes recent advances and significant applications in ILC methods for power grids, sensor networks and control processes Covers basic theory, rigorous mathematics as well as engineering practice

Machine Learning Control – Taming Nonlinear Dynamics and Turbulence

Machine Learning Control – Taming Nonlinear Dynamics and Turbulence
  • Author : Thomas Duriez,Steven L. Brunton,Bernd R. Noack
  • Publisher : Springer
  • Release Date : 2016-11-02
  • ISBN : 9783319406244
GET THIS BOOKMachine Learning Control – Taming Nonlinear Dynamics and Turbulence

This is the first textbook on a generally applicable control strategy for turbulence and other complex nonlinear systems. The approach of the book employs powerful methods of machine learning for optimal nonlinear control laws. This machine learning control (MLC) is motivated and detailed in Chapters 1 and 2. In Chapter 3, methods of linear control theory are reviewed. In Chapter 4, MLC is shown to reproduce known optimal control laws for linear dynamics (LQR, LQG). In Chapter 5, MLC detects and exploits a strongly nonlinear

Learning Control

Learning Control
  • Author : William Charles Messner
  • Publisher : Unknown
  • Release Date : 1992
  • ISBN : UCAL:C3369545
GET THIS BOOKLearning Control

Reinforcement Learning and Optimal Control

Reinforcement Learning and Optimal Control
  • Author : Dimitri Bertsekas
  • Publisher : Athena Scientific
  • Release Date : 2019-07-01
  • ISBN : 9781886529397
GET THIS BOOKReinforcement Learning and Optimal Control

This book considers large and challenging multistage decision problems, which can be solved in principle by dynamic programming (DP), but their exact solution is computationally intractable. We discuss solution methods that rely on approximations to produce suboptimal policies with adequate performance. These methods are collectively known by several essentially equivalent names: reinforcement learning, approximate dynamic programming, neuro-dynamic programming. They have been at the forefront of research for the last 25 years, and they underlie, among others, the recent impressive successes of

Linear and Nonlinear Iterative Learning Control

Linear and Nonlinear Iterative Learning Control
  • Author : Jian-Xin Xu,Ying Tan
  • Publisher : Springer
  • Release Date : 2003-09-04
  • ISBN : 9783540448457
GET THIS BOOKLinear and Nonlinear Iterative Learning Control

This monograph summarizes the recent achievements made in the field of iterative learning control. The book is self-contained in theoretical analysis and can be used as a reference or textbook for a graduate level course as well as for self-study. It opens a new avenue towards a new paradigm in deterministic learning control theory accompanied by detailed examples.

Motor Learning and Control for Practitioners

Motor Learning and Control for Practitioners
  • Author : Cheryl A. Coker
  • Publisher : Routledge
  • Release Date : 2017-09-22
  • ISBN : 9781351734622
GET THIS BOOKMotor Learning and Control for Practitioners

With an array of critical and engaging pedagogical features, the fourth edition of Motor Learning and Control for Practitioners offers the best practical introduction to motor learning available. This reader-friendly text approaches motor learning in accessible and simple terms, and lays a theoretical foundation for assessing performance; providing effective instruction; and designing practice, rehabilitation, and training experiences that promote skill acquisition. Features such as Exploration Activities and Cerebral Challenges involve students at every stage, while a broad range of examples

Intelligent Control: Principles, Techniques and Applications

Intelligent Control: Principles, Techniques and Applications
  • Author : Anonim
  • Publisher : Unknown
  • Release Date : 2022-10-02
  • ISBN : 9789814499323
GET THIS BOOKIntelligent Control: Principles, Techniques and Applications

Iterative Learning Control for Deterministic Systems

Iterative Learning Control for Deterministic Systems
  • Author : Kevin L. Moore
  • Publisher : Springer Science & Business Media
  • Release Date : 2012-12-06
  • ISBN : 9781447119128
GET THIS BOOKIterative Learning Control for Deterministic Systems

The material presented in this book addresses the analysis and design of learning control systems. It begins with an introduction to the concept of learning control, including a comprehensive literature review. The text follows with a complete and unifying analysis of the learning control problem for linear LTI systems using a system-theoretic approach which offers insight into the nature of the solution of the learning control problem. Additionally, several design methods are given for LTI learning control, incorporating a technique

Automation and Control

Automation and Control
  • Author : Constantin Volosencu,Serdar Küçük,José Guerrero,Oscar Valero
  • Publisher : BoD – Books on Demand
  • Release Date : 2021-04-21
  • ISBN : 9781839627132
GET THIS BOOKAutomation and Control

The book presents recent theoretical and practical information about the field of automation and control. It includes fifteen chapters that promote automation and control in practical applications in the following thematic areas: control theory, autonomous vehicles, mechatronics, digital image processing, electrical grids, artificial intelligence, and electric motor drives. The book also presents and discusses applications that improve the properties and performances of process control with examples and case studies obtained from real-world research in the field. Automation and Control is

European Control Conference 1993

European Control Conference 1993
  • Author : Anonim
  • Publisher : European Control Association
  • Release Date : 1993-06-28
  • ISBN : 0987654321XXX
GET THIS BOOKEuropean Control Conference 1993

Proceedings of the European Control Conference 1993, Groningen, Netherlands, June 28 – July 1, 1993

Bio-Inspired Collaborative Intelligent Control and Optimization

Bio-Inspired Collaborative Intelligent Control and Optimization
  • Author : Yongsheng Ding,Lei Chen,Kuangrong Hao
  • Publisher : Springer
  • Release Date : 2017-11-06
  • ISBN : 9789811066894
GET THIS BOOKBio-Inspired Collaborative Intelligent Control and Optimization

This book presents state-of-the-art research advances in the field of biologically inspired cooperative control theories and their applications. It describes various biologically inspired cooperative control and optimization approaches and highlights real-world examples in complex industrial processes. Multidisciplinary in nature and closely integrating theory and practice, the book will be of interest to all university researchers, control engineers and graduate students in intelligent systems and control who wish to learn the core principles, methods, algorithms, and applications.

Machine Learning Control by Symbolic Regression

Machine Learning Control by Symbolic Regression
  • Author : Askhat Diveev,Elizaveta Shmalko
  • Publisher : Springer Nature
  • Release Date : 2021-10-23
  • ISBN : 9783030832131
GET THIS BOOKMachine Learning Control by Symbolic Regression

This book provides comprehensive coverage on a new direction in computational mathematics research: automatic search for formulas. Formulas must be sought in all areas of science and life: these are the laws of the universe, the macro and micro world, fundamental physics, engineering, weather and natural disasters forecasting; the search for new laws in economics, politics, sociology. Accumulating many years of experience in the development and application of numerical methods of symbolic regression to solving control problems, the authors offer