Zeroing Neural Networks
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Zeroing Neural Networks
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Author : Lin Xiao
language : en
Publisher: John Wiley & Sons
Release Date : 2022-12-01
Zeroing Neural Networks written by Lin Xiao and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-01 with Computers categories.
Zeroing Neural Networks Describes the theoretical and practical aspects of finite-time ZNN methods for solving an array of computational problems Zeroing Neural Networks (ZNN) have become essential tools for solving discretized sensor-driven time-varying matrix problems in engineering, control theory, and on-chip applications for robots. Building on the original ZNN model, finite-time zeroing neural networks (FTZNN) enable efficient, accurate, and predictive real-time computations. Setting up discretized FTZNN algorithms for different time-varying matrix problems requires distinct steps. Zeroing Neural Networks provides in-depth information on the finite-time convergence of ZNN models in solving computational problems. Divided into eight parts, this comprehensive resource covers modeling methods, theoretical analysis, computer simulations, nonlinear activation functions, and more. Each part focuses on a specific type of time-varying computational problem, such as the application of FTZNN to the Lyapunov equation, linear matrix equation, and matrix inversion. Throughout the book, tables explain the performance of different models, while numerous illustrative examples clarify the advantages of each FTZNN method. In addition, the book: Describes how to design, analyze, and apply FTZNN models for solving computational problems Presents multiple FTZNN models for solving time-varying computational problems Details the noise-tolerance of FTZNN models to maximize the adaptability of FTZNN models to complex environments Includes an introduction, problem description, design scheme, theoretical analysis, illustrative verification, application, and summary in every chapter Zeroing Neural Networks: Finite-time Convergence Design, Analysis and Applications is an essential resource for scientists, researchers, academic lecturers, and postgraduates in the field, as well as a valuable reference for engineers and other practitioners working in neurocomputing and intelligent control.
Static And Dynamic Neural Networks
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Author : Madan Gupta
language : en
Publisher: John Wiley & Sons
Release Date : 2004-04-05
Static And Dynamic Neural Networks written by Madan Gupta and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-04-05 with Computers categories.
Neuronale Netze haben sich in vielen Bereichen der Informatik und künstlichen Intelligenz, der Robotik, Prozeßsteuerung und Entscheidungsfindung bewährt. Um solche Netze für immer komplexere Aufgaben entwickeln zu können, benötigen Sie solide Kenntnisse der Theorie statischer und dynamischer neuronaler Netze. Aneignen können Sie sie sich mit diesem Lehrbuch! Alle theoretischen Konzepte sind in anschaulicher Weise mit praktischen Anwendungen verknüpft. Am Ende jedes Kapitels können Sie Ihren Wissensstand anhand von Übungsaufgaben überprüfen.
Kinematic Control Of Redundant Robot Arms Using Neural Networks
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Author : Shuai Li
language : en
Publisher: John Wiley & Sons
Release Date : 2019-04-29
Kinematic Control Of Redundant Robot Arms Using Neural Networks written by Shuai Li and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-29 with Technology & Engineering categories.
Presents pioneering and comprehensive work on engaging movement in robotic arms, with a specific focus on neural networks This book presents and investigates different methods and schemes for the control of robotic arms whilst exploring the field from all angles. On a more specific level, it deals with the dynamic-neural-network based kinematic control of redundant robot arms by using theoretical tools and simulations. Kinematic Control of Redundant Robot Arms Using Neural Networks is divided into three parts: Neural Networks for Serial Robot Arm Control; Neural Networks for Parallel Robot Control; and Neural Networks for Cooperative Control. The book starts by covering zeroing neural networks for control, and follows up with chapters on adaptive dynamic programming neural networks for control; projection neural networks for robot arm control; and neural learning and control co-design for robot arm control. Next, it looks at robust neural controller design for robot arm control and teaches readers how to use neural networks to avoid robot singularity. It then instructs on neural network based Stewart platform control and neural network based learning and control co-design for Stewart platform control. The book finishes with a section on zeroing neural networks for robot arm motion generation. Provides comprehensive understanding on robot arm control aided with neural networks Presents neural network-based control techniques for single robot arms, parallel robot arms (Stewart platforms), and cooperative robot arms Provides a comparison of, and the advantages of, using neural networks for control purposes rather than traditional control based methods Includes simulation and modelling tasks (e.g., MATLAB) for onward application for research and engineering development By focusing on robot arm control aided by neural networks whilst examining central topics surrounding the field, Kinematic Control of Redundant Robot Arms Using Neural Networks is an excellent book for graduate students and academic and industrial researchers studying neural dynamics, neural networks, analog and digital circuits, mechatronics, and mechanical engineering.
Sliding Mode Control And Observation
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Author : Yuri Shtessel
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-01
Sliding Mode Control And Observation written by Yuri Shtessel and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-01 with Science categories.
The sliding mode control methodology has proven effective in dealing with complex dynamical systems affected by disturbances, uncertainties and unmodeled dynamics. Robust control technology based on this methodology has been applied to many real-world problems, especially in the areas of aerospace control, electric power systems, electromechanical systems, and robotics. Sliding Mode Control and Observation represents the first textbook that starts with classical sliding mode control techniques and progresses toward newly developed higher-order sliding mode control and observation algorithms and their applications. The present volume addresses a range of sliding mode control issues, including: *Conventional sliding mode controller and observer design *Second-order sliding mode controllers and differentiators *Frequency domain analysis of conventional and second-order sliding mode controllers *Higher-order sliding mode controllers and differentiators *Higher-order sliding mode observers *Sliding mode disturbance observer based control *Numerous applications, including reusable launch vehicle and satellite formation control, blood glucose regulation, and car steering control are used as case studies Sliding Mode Control and Observation is aimed at graduate students with a basic knowledge of classical control theory and some knowledge of state-space methods and nonlinear systems, while being of interest to a wider audience of graduate students in electrical/mechanical/aerospace engineering and applied mathematics, as well as researchers in electrical, computer, chemical, civil, mechanical, aeronautical, and industrial engineering, applied mathematicians, control engineers, and physicists. Sliding Mode Control and Observation provides the necessary tools for graduate students, researchers and engineers to robustly control complex and uncertain nonlinear dynamical systems. Exercises provided at the end of each chapter make this an ideal text for an advanced course taught in control theory.
Deep Reinforcement Learning With Guaranteed Performance
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Author : Yinyan Zhang
language : en
Publisher: Springer Nature
Release Date : 2019-11-09
Deep Reinforcement Learning With Guaranteed Performance written by Yinyan Zhang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-09 with Technology & Engineering categories.
This book discusses methods and algorithms for the near-optimal adaptive control of nonlinear systems, including the corresponding theoretical analysis and simulative examples, and presents two innovative methods for the redundancy resolution of redundant manipulators with consideration of parameter uncertainty and periodic disturbances. It also reports on a series of systematic investigations on a near-optimal adaptive control method based on the Taylor expansion, neural networks, estimator design approaches, and the idea of sliding mode control, focusing on the tracking control problem of nonlinear systems under different scenarios. The book culminates with a presentation of two new redundancy resolution methods; one addresses adaptive kinematic control of redundant manipulators, and the other centers on the effect of periodic input disturbance on redundancy resolution. Each self-contained chapter is clearly written, making the book accessible to graduate students as well as academic and industrial researchers in the fields of adaptive and optimal control, robotics, and dynamic neural networks.
Zhang Time Discretization Ztd Formulas And Applications
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Author : Yunong Zhang
language : en
Publisher: CRC Press
Release Date : 2024-08-07
Zhang Time Discretization Ztd Formulas And Applications written by Yunong Zhang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-07 with Computers categories.
This book aims to solve the discrete implementation problems of continuous-time neural network models while improving the performance of neural networks by using various Zhang Time Discretization (ZTD) formulas. The authors summarize and present the systematic derivations and complete research of ZTD formulas from special 3S-ZTD formulas to general NS-ZTD formulas. These finally lead to their proposed discrete-time Zhang neural network (DTZNN) algorithms, which are more efficient, accurate, and elegant. This book will open the door to scientific and engineering applications of ZTD formulas and neural networks, and will be a major inspiration for studies in neural network modeling, numerical algorithm design, prediction, and robot manipulator control. The book will benefit engineers, senior undergraduates, graduate students, and researchers in the fields of neural networks, computer mathematics, computer science, artificial intelligence, numerical algorithms, optimization, robotics, and simulation modeling.
Advances In Swarm Intelligence
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Author : Ying Tan
language : en
Publisher: Springer Nature
Release Date : 2024-08-20
Advances In Swarm Intelligence written by Ying Tan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-20 with Computers categories.
This two-volume set LNCS 14788 and 14789 constitutes the refereed post-conference proceedings of the 15th International Conference on Advances in Swarm Intelligence, ICSI 2024, held in Xining, China, during August 23–26, 2024. The 74 revised full papers presented in these proceedings were carefully reviewed and selected from 156 submissions. The papers are organized in the following topical sections: Part I - Particle swarm optimization; Swarm intelligence computing; Differential evolution; Evolutionary algorithms; Multi-agent reinforcement learning & Multi-objective optimization. Part II - Route planning problem; Machine learning; Detection and prediction; Classification; Edge computing; Modeling and optimization & Analysis of review.
Dynamic Neural Networks For Robot Systems Data Driven And Model Based Applications
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Author : Long Jin
language : en
Publisher: Frontiers Media SA
Release Date : 2024-07-24
Dynamic Neural Networks For Robot Systems Data Driven And Model Based Applications written by Long Jin and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-24 with Science categories.
Neural network control has been a research hotspot in academic fields due to the strong ability of computation. One of its wildly applied fields is robotics. In recent years, plenty of researchers have devised different types of dynamic neural network (DNN) to address complex control issues in robotics fields in reality. Redundant manipulators are no doubt indispensable devices in industrial production. There are various works on the redundancy resolution of redundant manipulators in performing a given task with the manipulator model information known. However, it becomes knotty for researchers to precisely control redundant manipulators with unknown model to complete a cyclic-motion generation CMG task, to some extent. It is worthwhile to investigate the data-driven scheme and the corresponding novel dynamic neural network (DNN), which exploits learning and control simultaneously. Therefore, it is of great significance to further research the special control features and solve challenging issues to improve control performance from several perspectives, such as accuracy, robustness, and solving speed.
Algebraic Informatics
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Author : Miroslav Ćirić
language : en
Publisher: Springer
Release Date : 2019-06-17
Algebraic Informatics written by Miroslav Ćirić and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-17 with Computers categories.
This book constitutes the refereed proceedings of the 8th International Conference on Algebraic Informatics, CAI 2019, held in Niš, Serbia, in June/July 2019. The 20 revised papers presented were carefully reviewed and selected from 35 submissions. The papers present research at the intersection of theoretical computer science, algebra, and related areas. They report original unpublished research and cover a broad range of topics from automata theory and logic, cryptography and coding theory, computer algebra, design theory, natural and quantum computation, and related areas.
Mathematical Analysis Optimization Approximation And Applications
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Author : Panos M Pardalos
language : en
Publisher: World Scientific
Release Date : 2025-01-17
Mathematical Analysis Optimization Approximation And Applications written by Panos M Pardalos and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-17 with Mathematics categories.
The comprehensive volume focuses on both research and survey papers presenting results in a broad spectrum of subjects in pure and applied mathematics, such as in approximation theory, optimization and their applications.Topics within this book include Sobolev spaces, Banach spaces, locally convex spaces, integral operators, Szasz-Mirakyan operators, to name a few.This useful reference text benefits professionals, academics, graduate students and advanced research scientists in theoretical computer science, computer mathematics and general applied mathematics. Effort was also made for the content to constitute a reference source for researchers in physics and engineering.