Author: Karl J. Aström Publisher: Springer Science & Business Media ISBN: 1447103491 Category : Technology & Engineering Languages : en Pages : 485
Book Description
The world of artificial systems is reaching complexity levels that es cape human understanding. Surface traffic, electricity distribution, air planes, mobile communications, etc. , are examples that demonstrate that we are running into problems that are beyond classical scientific or engi neering knowledge. There is an ongoing world-wide effort to understand these systems and develop models that can capture its behavior. The reason for this work is clear, if our lack of understanding deepens, we will lose our capability to control these systems and make they behave as we want. Researchers from many different fields are trying to understand and develop theories for complex man-made systems. This book presents re search from the perspective of control and systems theory. The book has grown out of activities in the research program Control of Complex Systems (COSY). The program has been sponsored by the Eu ropean Science Foundation (ESF) which for 25 years has been one of the leading players in stimulating scientific research. ESF is a European asso ciation of more than 60 leading national science agencies spanning more than 20 countries. ESF covers has standing committees in Medical Sci ences, Life and Environmental Sciences, Physical and Engineering Sci ences, Humanities and Social Sciences. The COSY program was ESF's first activity in the Engineering Sciences. The program run for a period of five years starting January 1995.
Author: Kyriakos Vamvoudakis Publisher: Butterworth-Heinemann ISBN: 0128054379 Category : Technology & Engineering Languages : en Pages : 764
Book Description
In the era of cyber-physical systems, the area of control of complex systems has grown to be one of the hardest in terms of algorithmic design techniques and analytical tools. The 23 chapters, written by international specialists in the field, cover a variety of interests within the broader field of learning, adaptation, optimization and networked control. The editors have grouped these into the following 5 sections: “Introduction and Background on Control Theory”, “Adaptive Control and Neuroscience”, “Adaptive Learning Algorithms”, “Cyber-Physical Systems and Cooperative Control”, “Applications”.The diversity of the research presented gives the reader a unique opportunity to explore a comprehensive overview of a field of great interest to control and system theorists. This book is intended for researchers and control engineers in machine learning, adaptive control, optimization and automatic control systems, including Electrical Engineers, Computer Science Engineers, Mechanical Engineers, Aerospace/Automotive Engineers, and Industrial Engineers. It could be used as a text or reference for advanced courses in complex control systems. • Collection of chapters from several well-known professors and researchers that will showcase their recent work • Presents different state-of-the-art control approaches and theory for complex systems • Gives algorithms that take into consideration the presence of modelling uncertainties, the unavailability of the model, the possibility of cooperative/non-cooperative goals and malicious attacks compromising the security of networked teams • Real system examples and figures throughout, make ideas concrete Includes chapters from several well-known professors and researchers that showcases their recent work Presents different state-of-the-art control approaches and theory for complex systems Explores the presence of modelling uncertainties, the unavailability of the model, the possibility of cooperative/non-cooperative goals, and malicious attacks compromising the security of networked teams Serves as a helpful reference for researchers and control engineers working with machine learning, adaptive control, and automatic control systems
Author: Aleksandar Zecevic Publisher: Springer Science & Business Media ISBN: 1441912169 Category : Science Languages : en Pages : 233
Book Description
"Control of Complex Systems: Structural Constraints and Uncertainty" focuses on control design under information structure constraints, with a particular emphasis on large-scale systems. The complexity of such systems poses serious computational challenges and severely restricts the types of feedback laws that can be used in practice. This book systematically addresses the main issues, and provides a number of applications that illustrate potential design methods, most which use Linear Matrix Inequalities (LMIs), which have become a popular design tool over the past two decades. Authors Aleksandar I. Zecevic and Dragoslav D. Siljak use their years of experience in the control field to also: Address the issues of large-scale systems as they relate to robust control and linear matrix inequalities Discuss a new approach to applying standard LMI techniques to large-scale systems, combining graphic-theoretic decomposition techniques with appropriate low-rank numerical approximations and dramatically reducing the computational effort Providing numerous examples and a wide variety of applications, ranging from electric power systems and nonlinear circuits to mechanical problems and dynamic Boolean networks "Control of Complex Systems: Structural Constraints and Uncertainty" will appeal to practicing engineers, researchers and students working in control design and other related areas.
Author: Petros A. Ioannou Publisher: CRC Press ISBN: 0849379865 Category : Medical Languages : en Pages : 552
Book Description
Comprehension of complex systems comes from an understanding of not only the behavior of constituent elements but how they act together to form the behavior of the whole. However, given the multidisciplinary nature of complex systems, the scattering of information across different areas creates a chaotic situation for those trying to understand pos
Author: Gorazd Karer Publisher: Springer ISBN: 3642339476 Category : Technology & Engineering Languages : en Pages : 261
Book Description
A predictive control algorithm uses a model of the controlled system to predict the system behavior for various input scenarios and determines the most appropriate inputs accordingly. Predictive controllers are suitable for a wide range of systems; therefore, their advantages are especially evident when dealing with relatively complex systems, such as nonlinear, constrained, hybrid, multivariate systems etc. However, designing a predictive control strategy for a complex system is generally a difficult task, because all relevant dynamical phenomena have to be considered. Establishing a suitable model of the system is an essential part of predictive control design. Classic modeling and identification approaches based on linear-systems theory are generally inappropriate for complex systems; hence, models that are able to appropriately consider complex dynamical properties have to be employed in a predictive control algorithm. This book first introduces some modeling frameworks, which can encompass the most frequently encountered complex dynamical phenomena and are practically applicable in the proposed predictive control approaches. Furthermore, unsupervised learning methods that can be used for complex-system identification are treated. Finally, several useful predictive control algorithms for complex systems are proposed and their particular advantages and drawbacks are discussed. The presented modeling, identification and control approaches are complemented by illustrative examples. The book is aimed towards researches and postgraduate students interested in modeling, identification and control, as well as towards control engineers needing practically usable advanced control methods for complex systems.
Author: H. Abou-Kandil Publisher: Springer Science & Business Media ISBN: 1475798539 Category : Technology & Engineering Languages : en Pages : 185
Book Description
Since the begining of the sixties, control theorists have developed a large body of knowledge concerning complex or large-scale systems theory. Using the state space approach, their purpose was to extend methods to cope with the increasingly sophisticated automation needs of man-made systems. Despite several remarkable contributions, and some successful applications, it can be stated that this theory has not yet become an engineering tool. On the other hand, the emergence of cheap and reliable microprocessors has profoundly transformed industrial instrumentation and control systems. Process control equipment is organized in multilevel distributed structures, closely related to the concepts introduced by complex systems control theory. This similarity should favor a fruitful intersection for practical applications. However, a gap still exists between the literature on control theory and the world of technological achievements. In the many books on complex systems, few have given attention to the technological aspects of a practical control problem. The present book is an attempt to fill this gap. To do this, it consistently reflects the viewpoints that: - Theory and technology are two indivisible facets of the same problem. -On-line implementation for real time applications is the ultimate goal of a control study.
Author: Fredmund Malik Publisher: Campus Verlag ISBN: 3593505398 Category : Business & Economics Languages : en Pages : 565
Book Description
"Malik demonstrates that management and management theory have strong foundations in systems science, and most specifically in a certain type of cybernetics of truly complex systems, of organismic, self-organizing, and evolving systems. This book provides the basics on how to create robust, functional, and sustainably viable systems. One of the reasons why it has become a classic on management cybernetics, now in its 11th edition, is that the strategies and heuristic principles of complexity management are still relevant - now more than ever."--Back cover.
Author: Jinhu Lü Publisher: Springer ISBN: 3662478242 Category : Technology & Engineering Languages : en Pages : 483
Book Description
This elementary book provides some state-of-the-art research results on broad disciplinary sciences on complex networks. It presents an in-depth study with detailed description of dynamics, controls and applications of complex networks. The contents of this book can be summarized as follows. First, the dynamics of complex networks, for example, the cluster dynamic analysis by using kernel spectral methods, community detection algorithms in bipartite networks, epidemiological modeling with demographics and epidemic spreading on multi-layer networks, are studied. Second, the controls of complex networks are investigated including topics like distributed finite-time cooperative control of multi-agent systems by applying homogenous-degree and Lyapunov methods, composite finite-time containment control for disturbed second-order multi-agent systems, fractional-order observer design of multi-agent systems, chaos control and anticontrol of complex systems via Parrondos game and many more. Third, the applications of complex networks provide some applicable carriers, which show the importance of theories developed in complex networks. In particular, a general model for studying time evolution of transition networks, deflection routing in complex networks, recommender systems for social networks analysis and mining, strategy selection in networked evolutionary games, integration and methods in computational biology, are discussed in detail.
Author: Azar, Ahmad Taher Publisher: IGI Global ISBN: 1799857905 Category : Mathematics Languages : en Pages : 685
Book Description
The current literature on dynamic systems is quite comprehensive, and system theory’s mathematical jargon can remain quite complicated. Thus, there is a need for a compendium of accessible research that involves the broad range of fields that dynamic systems can cover, including engineering, life sciences, and the environment, and which can connect researchers in these fields. The Handbook of Research on Modeling, Analysis, and Control of Complex Systems is a comprehensive reference book that describes the recent developments in a wide range of areas including the modeling, analysis, and control of dynamic systems, as well as explores related applications. The book acts as a forum for researchers seeking to understand the latest theory findings and software problem experiments. Covering topics that include chaotic maps, predictive modeling, random bit generation, and software bug prediction, this book is ideal for professionals, academicians, researchers, and students in the fields of electrical engineering, computer science, control engineering, robotics, power systems, and biomedical engineering.