Thank you for opening the second edition of this monograph, which is devoted to the study of a class of nonsmooth dynamical systems of the general form: ::i; = g(x,u) (0.
The purpose of this book is to present a self-contained and coordinated de- scription of several design methods for nonlinear control systems, with special emphasis on the problem of achieving stability, globally or on arbitrarily large domains, in the presence of model uncertainties.
Digital elements such as signal processors, microcontrollers or industrial PCs are widely used for filtering and control of continuous-time processes or plants.
With respect to the first edition as Volume 218 in the Lecture Notes in Con- trol and Information Sciences series the basic idea of the second edition has remained the same: to provide a compact presentation of some basic ideas in the classical theory of input-output and closed-loop stability, together with a choice of contributions to the recent theory of nonlinear robust and 1foo control and passivity-based control.
Over the past decades, although stochastic system control has been studied intensively within the field of control engineering, all the modelling and control strategies developed so far have concentrated on the performance of one or two output properties of the system.
As the use and relevance of robotics for countless scientific purposes grows all the time, research into the many diverse elements of the subject becomes ever more important and in demand.
Developed from a set of lecture notes by Professor Kamen and since developed and refined by both authors, this introductory yet comprehensive study is a prime example in its field.
Early and accurate fault detection and diagnosis for modern chemical plants can minimise downtime, increase the safety of plant operations, and reduce manufacturing costs.
Modern computer-based control systems are able to collect a large amount of information, display it to operators and store it in databases but the interpretation of the data and the subsequent decision making relies mainly on operators with little computer support.
Machine vision systems offer great potential in a large number of areas of manufacturing industry and are used principally for Automated Visual Inspection and Robot Vision.
Early and accurate fault detection and diagnosis for modern chemical plants can minimise downtime, increase the safety of plant operations, and reduce manufacturing costs.
In the increasingly competitive modern world, the industrial sector faces new challenges such as improving productivity and reducing costs while taking into account the process operational constraints.
Much has been written about the general difficulty of developing the models required for model-based control of processes whose dynamics exhibit signif- icant nonlinearity (for further discussion and references, see Chapter 1).
Hydraulic Servo-systems details the basic concepts of many recent developments of nonlinear identification and nonlinear control and their application to hydraulic servo-systems: developments such as feedback linearisation and fuzzy control.
Although the computing demands of real-time signal processing and control applications are increasing rapidly, parallel processors permit several instructions to be dealt with simultaneously so that the "e;real-time"e; needed is manageable.
Discrete-time Stochastic Systems gives a comprehensive introduction to the estimation and control of dynamic stochastic systems and provides complete derivations of key results such as the basic relations for Wiener filtering.
Relay feedback has attracted considerable research attention for more than a century but there has been no recent summary of the many newly-developed tools and results now available for this important area as a whole, those that have been published tending to focus on one process or controller type only.
A typical method of dealing with input and output constraints, especially for PID control, has been the empirical design and implementation of an intuitive solution to an individual plant and its constraints.
Mobile Robotics: A Practical Introduction (2nd edition) is an excellent introduction to the foundations and methods used for designing completely autonomous mobile robots.
An exposition of the interplay between the modelling of dynamic systems and the design of feedback controllers based on these models is the main goal of this book.
In the last decade new artificial intelligence methods for the modelling and control of complex systems, namely neural networks, fuzzy logic and probabilistic reasoning have drawn the interest of researchers and engineers.
With the rapid development of artificial intelligence and the emergence of various new sensors, autonomous driving has grown in popularity in recent years.
This book reflects the latest research trends, methods and experimental results in the field of Artificial Intelligence and Autonomous Transportation, which covers abundant state-of-the-art research theories and ideas.
This book reflects the latest research trends, methods and experimental results in the field of Artificial Intelligence and Autonomous Transportation, which covers abundant state-of-the-art research theories and ideas.
