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Autonomous Road Vehicle Path Planning and Tracking Control
  • Language: en
  • Pages: 260

Autonomous Road Vehicle Path Planning and Tracking Control

Discover the latest research in path planning and robust path tracking control In Autonomous Road Vehicle Path Planning and Tracking Control, a team of distinguished researchers delivers a practical and insightful exploration of how to design robust path tracking control. The authors include easy to understand concepts that are immediately applicable to the work of practicing control engineers and graduate students working in autonomous driving applications. Controller parameters are presented graphically, and regions of guaranteed performance are simple to visualize and understand. The book discusses the limits of performance, as well as hardware-in-the-loop simulation and experimental resu...

Autonomous Vehicles and Systems
  • Language: en
  • Pages: 464

Autonomous Vehicles and Systems

  • Type: Book
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  • Published: 2024-02-06
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  • Publisher: CRC Press

This book captures multidisciplinary research encompassing various facets of autonomous vehicle systems (AVS) research and developments. The AVS field is rapidly moving towards realization with numerous advances continually reported. The contributions to this field come from widely varying branches of knowledge, making it a truly multidisciplinary area of research and development. The topics covered in the book include: AI and deep learning for AVS Autonomous steering through deep neural networks Adversarial attacks and defenses on autonomous vehicles Gesture recognition for vehicle control Multi-sensor fusion in autonomous vehicles Teleoperation technologies for AVS Simulation and game theoretic decision making for AVS Path following control system design for AVS Hybrid cloud and edge solutions for AVS Ethics of AVS

Disturbance Observer for Advanced Motion Control with MATLAB / Simulink
  • Language: en
  • Pages: 292

Disturbance Observer for Advanced Motion Control with MATLAB / Simulink

A fulsome and robust presentation of disturbance observers complete with MATLAB sample programs and simulation results In Disturbance Observer for Advanced Motion Control with MATLAB/Simulink, distinguished electronics engineer Dr. Akira Shimada delivers a comprehensive exploration of the suppression of actual and unknown disturbances. In the book, you’ll find a systematic discussion of the basic theory and design methods of disturbance observers accompanied by instructive MATLAB and Simulink simulation examples. Included appendices cover the mathematical background of classical, modern, and digital control and ground the reader’s understanding of the more advanced sections. The included...

Sensorless Control of Permanent Magnet Synchronous Machine Drives
  • Language: en
  • Pages: 501

Sensorless Control of Permanent Magnet Synchronous Machine Drives

A comprehensive resource providing basic principles and state-of-the art developments in sensorless control technologies for permanent magnet synchronous machine drives Sensorless Control of Permanent Magnet Synchronous Machine Drives highlights the global research achievements over the last three decades and the sensorless techniques developed by the authors and their colleagues, and covers sensorless control techniques of permanent magnet machines, discussing issues and solutions. Many worked application examples are included to aid in practical understanding of concepts. Written by two pioneering authors in the field, Sensorless Control of Permanent Magnet Synchronous Machine Drives cover...

The Impact of Automatic Control Research on Industrial Innovation
  • Language: en
  • Pages: 260

The Impact of Automatic Control Research on Industrial Innovation

The Impact of Automatic Control Research on Industrial Innovation Bring together the theory and practice of control research with this innovative overview Automatic control research focuses on subjects pertaining to the theory and practice of automation science and technology subjects such as industrial automation, robotics, and human???machine interaction. With each passing year, these subjects become more relevant to researchers, policymakers, industrialists, and workers alike. The work of academic control researchers, however, is often distant from the perspectives of industry practitioners, creating the potential for insights to be lost on both sides. The Impact of Automatic Control Rese...

Advanced Control of Power Converters
  • Language: en
  • Pages: 468

Advanced Control of Power Converters

Advanced Control of Power Converters Unique resource presenting advanced nonlinear control methods for power converters, plus simulation, controller design, analyses, and case studies Advanced Control of Power Converters equips readers with the latest knowledge of three control methods developed for power converters: nonlinear control methods such as sliding mode control, Lyapunov-function-based control, and model predictive control. Readers will learn about the design of each control method, and simulation case studies and results will be presented and discussed to point out the behavior of each control method in different applications. In this way, readers wishing to learn these control me...

Dynamic System Modelling and Analysis with MATLAB and Python
  • Language: en
  • Pages: 340

Dynamic System Modelling and Analysis with MATLAB and Python

Dynamic System Modeling & Analysis with MATLAB & Python A robust introduction to the advanced programming techniques and skills needed for control engineering In Dynamic System Modeling & Analysis with MATLAB & Python: For Control Engineers, accomplished control engineer Dr. Jongrae Kim delivers an insightful and concise introduction to the advanced programming skills required by control engineers. The book discusses dynamic systems used by satellites, aircraft, autonomous robots, and biomolecular networks. Throughout the text, MATLAB and Python are used to consider various dynamic modeling theories and examples. The author covers a range of control topics, including attitude dynamics, attit...

Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities
  • Language: en
  • Pages: 239

Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities

This volume offers a wealth of interdisciplinary approaches to artificial intelligence, machine learning and optimization tools, which contribute to the optimization of urban features towards forming smart, sustainable, and livable future cities. Special features include: New research on the design of city elements and smart systems with respect to new technologies and scientific thinking Discussions on the theoretical background that lead to smart cities for the future New technologies and principles of research that can promote ideas of artificial intelligence and machine learning in optimized urban environments The book engages students and researchers in the subjects of artificial intelligence, machine learning, and optimization tools in smart sustainable cities as eminent international experts contribute their research results and thinking in its chapters. Overall, its audience can benefit from a variety of disciplines including, architecture, engineering, physics, mathematics, computer science, and related fields.

Automotive Applications of Hardware-in-the-Loop (HIL) Simulation
  • Language: en
  • Pages: 246

Automotive Applications of Hardware-in-the-Loop (HIL) Simulation

Automotive Applications of Hardware-in-the-Loop (HIL) Simulation shines a light on HIL simulation testing methodology commonly used in the automotive industry for conventional, electrification and autonomy applications and can serve as an introductory resource for college students looking to join the automotive industry or experienced technical professionals who need a deeper understanding on what is HIL simulation, what are its benefits and how can it be used in their respective organizations.

Model-Based Reinforcement Learning
  • Language: en
  • Pages: 276

Model-Based Reinforcement Learning

Model-Based Reinforcement Learning Explore a comprehensive and practical approach to reinforcement learning Reinforcement learning is an essential paradigm of machine learning, wherein an intelligent agent performs actions that ensure optimal behavior from devices. While this paradigm of machine learning has gained tremendous success and popularity in recent years, previous scholarship has focused either on theory—optimal control and dynamic programming – or on algorithms—most of which are simulation-based. Model-Based Reinforcement Learning provides a model-based framework to bridge these two aspects, thereby creating a holistic treatment of the topic of model-based online learning co...