Neural networks fundamentals in mobile robot control systems

Neural networks fundamentals in mobile robot control systems PDF

Author: Михаил Медведев

Publisher: Litres

Published: 2022-01-29

Total Pages: 146

ISBN-13: 5043371447

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Включает полное и систематизированное изложение материала по учебной программе курса «Интеллектуальные системы управления роботами». Адресован студентам, обучающимся по программам бакалавриата и магистратуры по специальности «Мехатроника и робототехника» Института радиотехники и систем управления Южного федерального университета. Включает темы, посвященные введению в нейронные сети, их применению, основам обучения нейронных сетей, многослойным нейронным сетям с прямой связью, передовым методам обучения нейронных сетей и варианты индивидуальных упражнений.

Neural Network Control Of Robot Manipulators And Non-Linear Systems

Neural Network Control Of Robot Manipulators And Non-Linear Systems PDF

Author: F W Lewis

Publisher: CRC Press

Published: 1998-11-30

Total Pages: 470

ISBN-13: 9780748405961

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There has been great interest in "universal controllers" that mimic the functions of human processes to learn about the systems they are controlling on-line so that performance improves automatically. Neural network controllers are derived for robot manipulators in a variety of applications including position control, force control, link flexibility stabilization and the management of high-frequency joint and motor dynamics. The first chapter provides a background on neural networks and the second on dynamical systems and control. Chapter three introduces the robot control problem and standard techniques such as torque, adaptive and robust control. Subsequent chapters give design techniques and Stability Proofs For NN Controllers For Robot Arms, Practical Robotic systems with high frequency vibratory modes, force control and a general class of non-linear systems. The last chapters are devoted to discrete- time NN controllers. Throughout the text, worked examples are provided.

High-level Feedback Control With Neural Networks

High-level Feedback Control With Neural Networks PDF

Author: Young Ho Kim

Publisher: World Scientific

Published: 1998-09-28

Total Pages: 228

ISBN-13: 9814496456

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Complex industrial or robotic systems with uncertainty and disturbances are difficult to control. As system uncertainty or performance requirements increase, it becomes necessary to augment traditional feedback controllers with additional feedback loops that effectively “add intelligence” to the system. Some theories of artificial intelligence (AI) are now showing how complex machine systems should mimic human cognitive and biological processes to improve their capabilities for dealing with uncertainty.This book bridges the gap between feedback control and AI. It provides design techniques for “high-level” neural-network feedback-control topologies that contain servo-level feedback-control loops as well as AI decision and training at the higher levels. Several advanced feedback topologies containing neural networks are presented, including “dynamic output feedback”, “reinforcement learning” and “optimal design”, as well as a “fuzzy-logic reinforcement” controller. The control topologies are intuitive, yet are derived using sound mathematical principles where proofs of stability are given so that closed-loop performance can be relied upon in using these control systems. Computer-simulation examples are given to illustrate the performance.

Neural Network Perception for Mobile Robot Guidance

Neural Network Perception for Mobile Robot Guidance PDF

Author: Dean A. Pomerleau

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 199

ISBN-13: 1461531926

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Dean Pomerleau's trainable road tracker, ALVINN, is arguably the world's most famous neural net application. It currently holds the world's record for distance traveled by an autonomous robot without interruption: 21.2 miles along a highway, in traffic, at speedsofup to 55 miles per hour. Pomerleau's work has received worldwide attention, including articles in Business Week (March 2, 1992), Discover (July, 1992), and German and Japanese science magazines. It has been featured in two PBS series, "The Machine That Changed the World" and "By the Year 2000," and appeared in news segments on CNN, the Canadian news and entertainment program "Live It Up", and the Danish science program "Chaos". What makes ALVINN especially appealing is that it does not merely drive - it learns to drive, by watching a human driver for roughly five minutes. The training inputstothe neural networkare a video imageoftheroad ahead and thecurrentposition of the steering wheel. ALVINN has learned to drive on single lane, multi-lane, and unpaved roads. It rapidly adapts to other sensors: it learned to drive at night using laser reflectance imaging, and by using a laser rangefinder it learned to swerve to avoid obstacles and maintain a fixed distance from a row of parked cars. It has even learned to drive backwards.

Radial Basis Function (RBF) Neural Network Control for Mechanical Systems

Radial Basis Function (RBF) Neural Network Control for Mechanical Systems PDF

Author: Jinkun Liu

Publisher: Springer Science & Business Media

Published: 2013-01-26

Total Pages: 375

ISBN-13: 3642348165

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Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to stable adaptive control system design using neural network approximation-based techniques. The main objectives of the book are to introduce the concrete design methods and MATLAB simulation of stable adaptive RBF neural control strategies. In this book, a broad range of implementable neural network control design methods for mechanical systems are presented, such as robot manipulators, inverted pendulums, single link flexible joint robots, motors, etc. Advanced neural network controller design methods and their stability analysis are explored. The book provides readers with the fundamentals of neural network control system design. This book is intended for the researchers in the fields of neural adaptive control, mechanical systems, Matlab simulation, engineering design, robotics and automation. Jinkun Liu is a professor at Beijing University of Aeronautics and Astronautics.

Model Abstraction in Dynamical Systems: Application to Mobile Robot Control

Model Abstraction in Dynamical Systems: Application to Mobile Robot Control PDF

Author: Patricia Mellodge

Publisher: Springer

Published: 2008-09-18

Total Pages: 126

ISBN-13: 3540707999

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The subject of this book is model abstraction of dynamical systems. The p- mary goal of the work embodied in this book is to design a controller for the mobile robotic car using abstraction. Abstraction provides a means to rep- sent the dynamics of a system using a simpler model while retaining important characteristics of the original system. A second goal of this work is to study the propagation of uncertain initial conditions in the framework of abstraction. The summation of this work is presented in this book. It includes the following: • An overview of the history and current research in mobile robotic control design. • A mathematical review that provides the tools used in this research area. • The development of the robotic car model and both controllers used in the new control design. • A review of abstraction and an extension of these ideas into new system relationship characterizations called traceability and -traceability. • A framework for designing controllers based on abstraction. • An open-loop control design with simulation results. • An investigation of system abstraction with uncertain initial conditions.

Adaptive Kinematic Control of Mobile Robot Based on Neural Networks

Adaptive Kinematic Control of Mobile Robot Based on Neural Networks PDF

Author: Al-Shibaany Zeyad Yousif Abdoon

Publisher: LAP Lambert Academic Publishing

Published: 2015-11-03

Total Pages: 124

ISBN-13: 9783659787713

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The applications of mobile robots have grown significantly during the last few years due to the fast development in sensors and microprocessors systems. These applications include material handling, hospital services, military applications ... etc. The need for a precise motion control becomes very crucial in order to support such applications. The adaptive motion control for mobile robot is one of the important areas of research. The design of an adaptive kinematic controller for a nonholonomic differential drive mobile robot based on neural network topology is considered in this work, and work is divided into three stages. Firstly, to identify the inverse kinematics behavior of the differential drive mobile robot system, the Multi-Layer Perceptron neural network has been used. The second stage is the simulation test to check the robustness of the controller. The final stage is the practical work. A National Instrument differential drive mobile robot platform has been used which is perfectly compatible with the LabVIEW2011 software. The controller is implemented in LabVIEW2011 and then deployed to the mobile robot kit through a wireless communication.

Computational Intelligence for Modelling, Control & Automation

Computational Intelligence for Modelling, Control & Automation PDF

Author: Masoud Mohammadian

Publisher: IOS Press

Published: 1999

Total Pages: 408

ISBN-13: 9789051994735

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Reliable and straightforward, this text has helped thousands of students learn to write well. Jean Wyrick's rhetorically organized STEPS TO WRITING WELL WITH ADDITIONAL READINGS is known for its student-friendly tone and the clear way it presents the basics of essay writing in an easy-to-follow progression of useful lessons and activities. Through straightforward advice and thoughtful assignments, the text gives students the practice they need to approach writing well-constructed essays with confidence. With Wyrick's helpful instruction and the book's professional samples by both well-known classic and contemporary writers, STEPS TO WRITING WELL WITH ADDITIONAL READINGS sets students on a solid path to writing success. Everything students need to begin, organize, and revise writing--from choosing a topic to developing the essay to polishing prose--is right here In the ninth edition, Wyrick updates and refines the book's successful approach, adding useful new discussions, readings, exercises, essay assignments, and visual images for analysis.

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