Modelling and Control for Intelligent Industrial Systems: Adaptive Algorithms in Robotics and Industrial Engineering

ISBN-13: 9783642178740 / Angielski / Twarda / 2011 / 379 str.

Gerasimos Rigatos

Opis

: Incorporating intelligence in industrial systems can help to increase productivity, cut-off production costs, and to improve working conditions and safety in industrial environments. This need has resulted in the rapid development of modeling and control methods for industrial systems and robots, of fault detection and isolation methods for the prevention of critical situations in industrial work-cells and production plants, of optimization methods aiming at a more profitable functioning of industrial installations and robotic devices and of machine intelligence methods aiming at reducing human intervention in industrial systems operation. To this end, the book analyzes and extends some main directions of research in modeling and control for industrial systems.

Recenzje

From the reviews:

"The present book defines and analyzes some main directions of research in modeling and control for industrial systems. ... The book may serve as a tool for students, scientists and engineers from academia and industry experienced in these attractive areas. It can be also a source for courses, which can be part of the academic programme of Electrical, Mechanical, Industrial Engineering and Computer Science Departments." (Clementina Mladenova, Zentralblatt MATH, Vol. 1217, 2011)

Spis treści

Industrial robots in contact-free operation.- Industrial robots in compliance tasks.- Mobile robots and autonomous vehicles.- Adaptive control methods for industrial systems .-Robust control methods for industrial systems.- Filtering and estimation methods for industrial systems.- Sensor fusion-based control for industrial systems.- Fault detection and isolation for industrial systems.- Application of fault diagnosis to industrial systems.- Optimization methods for motion planning of multi-robot systems.- Optimization methods for target tracking by multi-robot systems.- Optimization methods for industrial automation.- Machine learning methods for industrial systems control.- Machine learning methods for industrial systems fault diagnosis.- Applications of machine vision to industrial systems.

Blurb

Incorporating intelligence in industrial systems can help to increase productivity, cut-off production costs, and to improve working conditions and safety in industrial environments. This need has resulted in the rapid development of modeling and control methods for industrial systems and robots, of fault detection and isolation methods for the prevention of critical situations in industrial work-cells and production plants, of optimization methods aiming at a more profitable functioning of industrial installations and robotic devices and of machine intelligence methods aiming at reducing human intervention in industrial systems operation.

To this end, the book analyzes and extends some main directions of research in modeling and control for industrial systems. These are: (i) industrial robots, (ii) mobile robots and autonomous vehicles, (iii) adaptive and robust control of electromechanical systems, (iv) filtering and stochastic estimation for multisensor fusion and sensorless control of industrial systems (iv) fault detection and isolation in robotic and industrial systems, (v) optimization in industrial automation and robotic systems design, and (vi) machine intelligence for robots autonomy. The book will be a useful companion to engineers and researchers since it covers a wide spectrum of problems in the area of industrial systems. Moreover, the book is addressed to undergraduate and post-graduate students, as an upper-level course supplement of automatic control and robotics courses.