Pedro Albertos – författare

The world of artificial systems is reaching complexity levels that es­ cape human understanding. Researchers from many different fields are trying to understand and develop theories for complex man-made systems. The book has grown out of activities in the research program Control of Complex Systems (COSY).

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.

The world of artificial systems is reaching hitherto undreamed-of levels of complexity. Surface traffic, electricity distribution, mobile communications, etc., demonstrate that problems are arising that are beyond classical scientific or engineering knowledge. In order that our ability to control such systems should not be hindered by lack of comprehension, there is an on-going effort to understand them.This book is an example of the types of approach that European researchers are using to tackle problems derived from systems' complexity. It has grown out of activities in the Control of Complex Systems (COSY) research program the goals of which are to promote multi-disciplinary activity leading to a deeper understanding and further development of control technologies for complex systems and if possible, to develop the theory underlying such systems. The material in this book represents a selection of the results of the COSY program and is organised as a collection of essays of varying nature: surveys of essential areas, discussion of specific problems, case studies, and benchmark problems.Topics covered include:Modelling complex physical systems;Passivity-based control of non-linear systems;Aspects of fault identification and fault tolerance;Control design;Learning control;Satellite attitude control.Complex systems appear in many different fields and for this reason this book should be of interest to scientists, researchers and industrial engineers with a broad spectrum of experience.

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. The combination of both subjects into a cohesive development allows the consistent treatment of both problems to yield powerful new tools for the improvement of system performance. Central among the themes of this work is the observation that operation of a system in feedback with a controller exposes the areas in which the model fit is constraining the controller performance achieved. The book presents new techniques for the understanding of the iterative improvement of performance through the successive fitting of models using closed-loop data and the design of high-performance controllers using these models.The subject matter includes: New approaches to understanding how to affect the fit of dynamical models to physical processes through the choice of experiments, data pre-filtering and model structure; connections between robust control design methods and their dependency on the quality of model fit; experimental design in which data collected in operation under feedback can reveal areas that limit the performance achieved; iterative approaches to link these model-fitting and control design phases in a cogent manner so as to achieve improved performance overall. The authors of individual chapters are some of the most renowned and authoritative figures in the fields of system identification and control design.

Multivariable control techniques solve issues of complex specification and modelling errors elegantly but the complexity of the underlying mathematics is much higher than presented in traditional single-input, single-output control courses. Multivariable Control Systems focuses on control design with continual references to the practical aspects of implementation. While the concepts of multivariable control are justified, the book emphasises the need to maintain student interest and motivation over exhaustively rigorous mathematical proof. Tools of analysis and representation are always developed as methods for achieving a final control system design and evaluation. Features: - design implementation clearly laid out using extensive reference to Matlab; - combined consideration of systems (plant) and signals (mainly disturbances) in a fluent but simple presentation; - step-by-step approach from the objectives of multivariable control to the solution of complete design problems. Multivariable Control Systems is an ideal text for masters students, students beginning their Ph.D. or for final-year undergraduates looking for more depth than provided by introductory textbooks.It will also interest the control engineer practising in industry and seeking to implement robust or multivariable control solutions to plant problems in as straightforward a manner as possible.

Examples of applications of LABC to systems in real operating conditions (mobile robots, marine vessels, quadrotor and pvtol aircraft, chemical reactors and First Order Plus Dead Time systems) illustrate the controller design in such a way that the reader attains an understanding of LABC.

Examples of applications of LABC to systems in real operating conditions (mobile robots, marine vessels, quadrotor and pvtol aircraft, chemical reactors and First Order Plus Dead Time systems) illustrate the controller design in such a way that the reader attains an understanding of LABC.