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Control of Self-Organizing Nonlinear Systems

Author: Eckehard Schöll

Publisher: Springer

Published: 2016-01-22

Total Pages: 478

ISBN-13: 3319280287

The book summarizes the state-of-the-art of research on control of self-organizing nonlinear systems with contributions from leading international experts in the field. The first focus concerns recent methodological developments including control of networks and of noisy and time-delayed systems. As a second focus, the book features emerging concepts of application including control of quantum systems, soft condensed matter, and biological systems. Special topics reflecting the active research in the field are the analysis and control of chimera states in classical networks and in quantum systems, the mathematical treatment of multiscale systems, the control of colloidal and quantum transport, the control of epidemics and of neural network dynamics.

Self-Organized Biological Dynamics and Nonlinear Control

Author: Jan Walleczek

Publisher: Cambridge University Press

Published: 2006-04-20

Total Pages: 444

ISBN-13: 1139427598

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The growing impact of nonlinear science on biology and medicine is fundamentally changing our view of living organisms and disease processes. This book introduces the application to biomedicine of a broad range of interdisciplinary concepts from nonlinear dynamics, such as self-organization, complexity, coherence, stochastic resonance, fractals and chaos. It comprises 18 chapters written by leading figures in the field and covers experimental and theoretical research, as well as the emerging technological possibilities such as nonlinear control techniques for treating pathological biodynamics, including heart arrhythmias and epilepsy. This book will attract the interest of professionals and students from a wide range of disciplines, including physicists, chemists, biologists, sensory physiologists and medical researchers such as cardiologists, neurologists and biomedical engineers.

Multiple Modeling and Control of Nonlinear Systems with Self-organizing Maps

Author: Jeongho Cho

Publisher:

Published: 2004

Total Pages:

ISBN-13:

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Based on the identified multiple models, the problem of designing controllers is discussed. Each local linear model is associated with a linear controller, which is easy to design. Switching of the controllers is done synchronously with the active local linear model that tracks different operating conditions. The effectiveness of the proposed approach is shown through experiments for modeling complex nonlinear plants such as chaotic systems, nonlinear discrete time systems and flight vehicles. Its comparison with neural networks-based alternatives, Time Delay Neural Network (TDNN), shows clear advantages of local modeling and control in terms of performance.

Self-organizing and Optimal Control for Nonlinear Systems

Author: Wenjie Dong

Publisher:

Published: 2009

Total Pages: 87

ISBN-13:

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Vehicle formation control is one of important research topics in transportation. Control of uncertain nonlinear systems is one of fundamental problems in vehicle control. In this dissertation, we consider this fundamental control problem. Specially, we considered self-organizing based tracking control of uncertain nonaffine systems and optimal control of uncertain nonlinear systems. In tracking control of nonaffine systems, a self-organizing online approximation based controller is proposed to achieve a prespecified tracking accuracy, without using high-gain control nor large magnitude switching. For optimal control of uncertain nonlinear systems, we considered point-wise min-norm optimal control of uncertain nonlinear systems and approximately optimal control of uncertain nonlinear systems. In point-wise non-norm optimal control, optimal regulation and optimal tracking controllers were proposed with the aid of locally weighted learning observers. By introducing control Lyapunov functions and redefining the optimal criterions, analytic controllers were proposed and were optimal in the sense of min-norm. In approximately optimal control of uncertain nonlinear systems, adaptive optimal controllers were proposed with the aid of iterative approximation techniques and adaptive control. By iteratively learning, the difficulty of solving Hamilton-Jacobian-Bellman (HJB) equation is overcome. The proposed adaptive optimal algorithms can be applied to solve optimal control problem of a large class of nonlinear systems. To show effectiveness of the proposed controllers for above problems, simulations were done in computers.

Self-organized Motion

Author: Satoshi Nakata

Publisher: Royal Society of Chemistry

Published: 2018-11-01

Total Pages: 388

ISBN-13: 1788015436

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Self-propelled objects (particles, droplets) are autonomous agents that can convert energy from the environment into motion. These motions include nonlinear behaviour such as oscillations, synchronization, bifurcation, and pattern formation. In recent years, there has been much interest in self-propelled objects for their potential role in mass transport or their use as carriers in confined spaces. An improved understanding of self-organized motion has even allowed researchers to design objects for specific motion. This book gives an overview of the principles of self-propelled motion in chemical objects (particles, droplets) far from their thermodynamic equilibrium, at various spatial scales. Theoretical aspects, the characteristics of the motion and the design procedures of such systems are discussed from the viewpoint of nonlinear dynamics and examples of applications for these nonlinear systems are provided. This book is suitable for researchers and graduate students interested in physical and theoretical chemistry as well as soft matter.

Design and Control of Self-organizing Systems

Author: Carlos Gershenson

Publisher: CopIt ArXives

Published: 2007-09-05

Total Pages: 189

ISBN-13: 0983117233

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Complex systems are usually difficult to design and control. There are several particular methods for coping with complexity, but there is no general approach to build complex systems. In this book I propose a methodology to aid engineers in the design and control of complex systems. This is based on the description of systems as self-organizing. Starting from the agent metaphor, the methodology proposes a conceptual framework and a series of steps to follow to find proper mechanisms that will promote elements to find solutions by actively interacting among themselves.

Identification and Control of Nonlinear Systems Using Multiple Models Based on the Self-organizing Map (SOM)

Author: Geetha K. Thampi

Publisher:

Published: 2003

Total Pages:

ISBN-13:

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ABSTRACT: This thesis addresses the problem of modeling and controlling non-linear plants by utilizing a self-organizing map (SOM). It uses multiple models of the non-linear plant for identification, as well as a multi-model controller. The SOM is used to cluster the input space and it elegantly divides the space into regions that individually represents the local dynamics. The local models are then derived using least square fit for every SOM Processing Element (PE). Hence the global dynamics is represented by a set of local models. Multiple switching controllers are designed for these models using LMS algorithm. The switching between different controllers is performed by the SOM based on the present state of the system. The proposed methodology is tested on various nonlinear systems to demonstrate its performance. In the later part of the thesis, optimality is brought into controller design through adaptive critic methods. Dual Heuristic Dynamic Programming (DHP), a member of the adaptive critic family, is explored in detail and is implemented in the multiple model setting to design a globally optimal controller for nonlinear systems.

Advanced Topics on Cellular Self-organizing Nets and Chaotic Nonlinear Dynamics to Model and Control Complex Systems

Author: Riccardo Caponetto

Publisher: World Scientific

Published: 2008

Total Pages: 208

ISBN-13: 9812814043

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This book focuses on the research topics investigated during the three-year research project funded by the Italian Ministero dell'Istruzione, dell'Universit e della Ricerca (MIUR: Ministry of Education, University and Research) under the FIRB project RBNE01CW3M. With the aim of introducing newer perspectives of the research on complexity, the final results of the project are presented after a general introduction to the subject. The book is intended to provide researchers, PhD students, and people involved in research projects in companies with the basic fundamentals of complex systems and the advanced project results recently obtained.

Self-organizing Control of Stochastic Systems

Author: George N. Saridis

Publisher:

Published: 1977

Total Pages: 518

ISBN-13:

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Self-Organizing Systems

Author: F.Eugene Yates

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 658

ISBN-13: 1461308836

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Technological systems become organized by commands from outside, as when human intentions lead to the building of structures or machines. But many nat ural systems become structured by their own internal processes: these are the self organizing systems, and the emergence of order within them is a complex phe nomenon that intrigues scientists from all disciplines. Unfortunately, complexity is ill-defined. Global explanatory constructs, such as cybernetics or general sys tems theory, which were intended to cope with complexity, produced instead a grandiosity that has now, mercifully, run its course and died. Most of us have become wary of proposals for an "integrated, systems approach" to complex matters; yet we must come to grips with complexity some how. Now is a good time to reexamine complex systems to determine whether or not various scientific specialties can discover common principles or properties in them. If they do, then a fresh, multidisciplinary attack on the difficulties would be a valid scientific task. Believing that complexity is a proper scientific issue, and that self-organizing systems are the foremost example, R. Tomovic, Z. Damjanovic, and I arranged a conference (August 26-September 1, 1979) in Dubrovnik, Yugoslavia, to address self-organizing systems. We invited 30 participants from seven countries. Included were biologists, geologists, physicists, chemists, mathematicians, bio physicists, and control engineers. Participants were asked not to bring manu scripts, but, rather, to present positions on an assigned topic. Any writing would be done after the conference, when the writers could benefit from their experi ences there.