Dynamic Centralized and Decentralized Control Systems

Dynamic Centralized and Decentralized Control Systems PDF Author: Douglas P. Looze
Publisher:
ISBN:
Category : Express highways
Languages : en
Pages :

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Book Description
Application to a freeway corridor.

Dynamic Centralized and Decentralized Control Systems

Dynamic Centralized and Decentralized Control Systems PDF Author: Douglas P. Looze
Publisher:
ISBN:
Category : Express highways
Languages : en
Pages :

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Book Description
Application to a freeway corridor.

Decentralized Control of Stochastic Dynamic Systems with Applications to Resource Allocation and Portfolio Management

Decentralized Control of Stochastic Dynamic Systems with Applications to Resource Allocation and Portfolio Management PDF Author: Huaning Cai
Publisher:
ISBN:
Category :
Languages : en
Pages : 182

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Book Description
Modern engineering and social systems are often too complex to be managed by a centralized agent. Instead, such systems are commonly structured with multiple decentralized agents each responsible for managing a subset of the system, but the resulting system performance depends on the aggregate of the decisions made by decentralized agents. Local agents' decision makings often exhibit selfish behavior as they seek to optimize their own objectives under their localized models, which if left uncoordinated can lead to substantial loss of efficiency compared with the system that can be optimized by a single (hypothetical) centralized agent. In this dissertation, we seek to study the fundamental issues of how to efficiently manage large-scale and multi-agent stochastic dynamic systems, especially on how to device efficient coordination mechanisms that would optimize system performance under various constraints that are unique to decentralized systems. In the first part of this dissertation we study decentralized control of a general class of stochastic dynamic resource allocation problems that have many applications. We consider a stochastic system in which multiple decentralized agents allocate shared system resources in response to customer requests that arrive stochastically over time. Each agent is responsible for a subset of the allocation decisions which it makes according to a dynamic allocation policy obtained by maximizing his own expected profit subject to a potentially mis-specified model of the way in which shared resources are consumed by other agents. We introduce the notion of a transfer contract which specifies how agents compensate one another whenever resources are consumed and establish the existence of contracts under which the decentralized system has no efficiency loss relative to centralized optimality. We also show that this property is insensitive to mis-specification by each agent of the dynamics of resource consumption by others in the system. An explicit characterization of the optimal transfer contract and an iterative decentralized algorithm for computing it is also provided. In the language of duality, contracts are analogous to shadow prices and the iterative algorithm has the favor of a dual update method, but strong duality and convergence of the iterative algorithm to the set of optimal contracts are guaranteed without assumptions of convexity. In the second part of this dissertation we study a class of related decentralized control problems but specialize to portfolio and risk management. Many financial institutions typically trade in multiple correlated markets. While centralized portfolio optimization over all trading decisions is ideal, it is generally not possible due to the complexity of each market, and firms typically adopt a decentralized setup in which trading in each market the responsibility of a particular desk. Decentralized portfolio optimization, however, is complicated by the fact that different agents are commonly only well informed about their own investment universe (proprietary research and forecasts, etc) and prefer to keep this private, and have their own incentives which they optimize on the basis of their limited models. It is well known, however, that the aggregate performance of such a system can be extremely inefficient due to the loss of diversification. In this dissertation, we formulate a multi-agent dynamic portfolio choice problem and study how to improve its efficiency. We show that an internal system of swap contracts, which define internal cash transfers between agents, can be used to facilitate risk sharing and induce agents to choose portfolios that as a collection are optimal for the firm. Conceptually using swap contracts is similar to performance benchmarking that is often employed in the finance literature for decentralized portfolio management, but our new approach offers a significant advantage in that the swap contracts can be constructed in decentralized manner without requiring an all-knowing central agent. We provide an explicit characterization of the optimal swap contracts and an iterative algorithm for computing them that can be implemented without compromising proprietary agent level data. Throughout this dissertation, we also discuss various important issues surrounding decentralized control of stochastic dynamic systems, including but not limited to approximation methods, performance attribution, sensitivity analysis, and fairness issues, etc.

Control and Dynamic Systems V22

Control and Dynamic Systems V22 PDF Author: C.T. Leonides
Publisher: Elsevier
ISBN: 0323162851
Category : Technology & Engineering
Languages : en
Pages : 419

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Book Description
Control and Dynamic Systems, Volume 22: Decentralized/Distributed Control and Dynamic Systems, Part 1 deals with advances in techniques for the analysis and synthesis of decentralized or distributed control and dynamic systems. This book begins with a unique presentation of important results and techniques that decentralized control systems often face due to the fact that the individual systems in a collection or set of decentralized control systems are somewhat incomplete. The controllability, observability, implications, and powerful techniques for stabilization and control of decentralized systems are also discussed. The next chapters describe the covariance equivalent realizations with application to model reductions of large-scale systems and decentralized estimation and control of one-way connected subsystems. This publication concludes with a presentation of the multivariable feedback and decentralized control that reviews fundamental results extending multivariable theory from conventional control systems to the highly challenging problems of decentralized control. This volume is beneficial to students and researchers conducting work on decentralized or distributed control and dynamic systems.

Decentralized Estimation and Control for Multisensor Systems

Decentralized Estimation and Control for Multisensor Systems PDF Author: Arthur G.O. Mutambara
Publisher: Routledge
ISBN: 1351456490
Category : Technology & Engineering
Languages : en
Pages : 252

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Book Description
Decentralized Estimation and Control for Multisensor Systems explores the problem of developing scalable, decentralized estimation and control algorithms for linear and nonlinear multisensor systems. Such algorithms have extensive applications in modular robotics and complex or large scale systems, including the Mars Rover, the Mir station, and Space Shuttle Columbia. Most existing algorithms use some form of hierarchical or centralized structure for data gathering and processing. In contrast, in a fully decentralized system, all information is processed locally. A decentralized data fusion system includes a network of sensor nodes - each with its own processing facility, which together do not require any central processing or central communication facility. Only node-to-node communication and local system knowledge are permitted. Algorithms for decentralized data fusion systems based on the linear information filter have been developed, obtaining decentrally the same results as those in a conventional centralized data fusion system. However, these algorithms are limited, indicating that existing decentralized data fusion algorithms have limited scalability and are wasteful of communications and computation resources. Decentralized Estimation and Control for Multisensor Systems aims to remove current limitations in decentralized data fusion algorithms and to extend the decentralized principle to problems involving local control and actuation. The text discusses: Generalizing the linear Information filter to the problem of estimation for nonlinear systems Developing a decentralized form of the algorithm Solving the problem of fully connected topologies by using generalized model distribution where the nodal system involves only locally relevant states Reducing computational requirements by using smaller local model sizes Defining internodal communication Developing estima

Decentralized Neural Control: Application to Robotics

Decentralized Neural Control: Application to Robotics PDF Author: Ramon Garcia-Hernandez
Publisher: Springer
ISBN: 3319533126
Category : Technology & Engineering
Languages : en
Pages : 121

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Book Description
This book provides a decentralized approach for the identification and control of robotics systems. It also presents recent research in decentralized neural control and includes applications to robotics. Decentralized control is free from difficulties due to complexity in design, debugging, data gathering and storage requirements, making it preferable for interconnected systems. Furthermore, as opposed to the centralized approach, it can be implemented with parallel processors. This approach deals with four decentralized control schemes, which are able to identify the robot dynamics. The training of each neural network is performed on-line using an extended Kalman filter (EKF). The first indirect decentralized control scheme applies the discrete-time block control approach, to formulate a nonlinear sliding manifold. The second direct decentralized neural control scheme is based on the backstepping technique, approximated by a high order neural network. The third control scheme applies a decentralized neural inverse optimal control for stabilization. The fourth decentralized neural inverse optimal control is designed for trajectory tracking. This comprehensive work on decentralized control of robot manipulators and mobile robots is intended for professors, students and professionals wanting to understand and apply advanced knowledge in their field of work.

Decentralized Control of Complex Systems

Decentralized Control of Complex Systems PDF Author: S?iljak
Publisher: Academic Press
ISBN: 0080958710
Category : Computers
Languages : en
Pages : 543

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Book Description
Decentralized Control of Complex Systems

Decentralized/distributed Control and Dynamic Systems

Decentralized/distributed Control and Dynamic Systems PDF Author: Cornelius T. Leondes
Publisher:
ISBN:
Category : Feedback control systems
Languages : en
Pages : 323

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Book Description


Global Stability through Decentralization?

Global Stability through Decentralization? PDF Author: Peter A. Wilderer
Publisher: Springer
ISBN: 3319243586
Category : Science
Languages : en
Pages : 225

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Book Description
The authors of this book, who represent a broad range of scientific disciplines, discuss the issue of centralized versus decentralized control and regulation in the context of sustainable development. The stability and resilience of complex technical, economic, societal and political systems are commonly assumed to be highly dependent on the effectiveness of sophisticated, mainly centralized regulation and control systems and governance structures, respectively. In nature, however, life is mainly self-regulated by widespread, mainly DNA-encoded control mechanisms. The fact that life has endured for more than 2.4 billion years suggests that, for man-made systems, decentralized control concepts are superior to centralized ones. The authors discuss benefits and drawbacks of both approaches to achieving sustainability, providing valuable information for students and professional decision makers alike.

Stochastic Networked Control Systems

Stochastic Networked Control Systems PDF Author: Serdar Yüksel
Publisher: Springer Science & Business Media
ISBN: 1461470854
Category : Mathematics
Languages : en
Pages : 491

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Book Description
Networked control systems are increasingly ubiquitous today, with applications ranging from vehicle communication and adaptive power grids to space exploration and economics. The optimal design of such systems presents major challenges, requiring tools from various disciplines within applied mathematics such as decentralized control, stochastic control, information theory, and quantization. A thorough, self-contained book, Stochastic Networked Control Systems: Stabilization and Optimization under Information Constraints aims to connect these diverse disciplines with precision and rigor, while conveying design guidelines to controller architects. Unique in the literature, it lays a comprehensive theoretical foundation for the study of networked control systems, and introduces an array of concrete tools for work in the field. Salient features included: · Characterization, comparison and optimal design of information structures in static and dynamic teams. Operational, structural and topological properties of information structures in optimal decision making, with a systematic program for generating optimal encoding and control policies. The notion of signaling, and its utilization in stabilization and optimization of decentralized control systems. · Presentation of mathematical methods for stochastic stability of networked control systems using random-time, state-dependent drift conditions and martingale methods. · Characterization and study of information channels leading to various forms of stochastic stability such as stationarity, ergodicity, and quadratic stability; and connections with information and quantization theories. Analysis of various classes of centralized and decentralized control systems. · Jointly optimal design of encoding and control policies over various information channels and under general optimization criteria, including a detailed coverage of linear-quadratic-Gaussian models. · Decentralized agreement and dynamic optimization under information constraints. This monograph is geared toward a broad audience of academic and industrial researchers interested in control theory, information theory, optimization, economics, and applied mathematics. It could likewise serve as a supplemental graduate text. The reader is expected to have some familiarity with linear systems, stochastic processes, and Markov chains, but the necessary background can also be acquired in part through the four appendices included at the end. · Characterization, comparison and optimal design of information structures in static and dynamic teams. Operational, structural and topological properties of information structures in optimal decision making, with a systematic program for generating optimal encoding and control policies. The notion of signaling, and its utilization in stabilization and optimization of decentralized control systems. · Presentation of mathematical methods for stochastic stability of networked control systems using random-time, state-dependent drift conditions and martingale methods. · Characterization and study of information channels leading to various forms of stochastic stability such as stationarity, ergodicity, and quadratic stability; and connections with information and quantization theories. Analysis of various classes of centralized and decentralized control systems. · Jointly optimal design of encoding and control policies over various information channels and under general optimization criteria, including a detailed coverage of linear-quadratic-Gaussian models. · Decentralized agreement and dynamic optimization under information constraints. This monograph is geared toward a broad audience of academic and industrial researchers interested in control theory, information theory, optimization, economics, and applied mathematics. It could likewise serve as a supplemental graduate text. The reader is expected to have some familiarity with linear systems, stochastic processes, and Markov chains, but the necessary background can also be acquired in part through the four appendices included at the end.

Coordination Control of Distributed Systems

Coordination Control of Distributed Systems PDF Author: Jan H. van Schuppen
Publisher: Springer
ISBN: 3319104071
Category : Technology & Engineering
Languages : en
Pages : 393

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Book Description
This book describes how control of distributed systems can be advanced by an integration of control, communication, and computation. The global control objectives are met by judicious combinations of local and nonlocal observations taking advantage of various forms of communication exchanges between distributed controllers. Control architectures are considered according to increasing degrees of cooperation of local controllers: fully distributed or decentralized control, control with communication between controllers, coordination control, and multilevel control. The book covers also topics bridging computer science, communication, and control, like communication for control of networks, average consensus for distributed systems, and modeling and verification of discrete and of hybrid systems. Examples and case studies are introduced in the first part of the text and developed throughout the book. They include: control of underwater vehicles, automated-guided vehicles on a container terminal, control of a printer as a complex machine, and control of an electric power system. The book is composed of short essays each within eight pages, including suggestions and references for further research and reading. By reading the essays collected in the book Coordination Control of Distributed Systems, graduate students and post-docs will be introduced to the research frontiers in control of decentralized and of distributed systems. Control theorists and practitioners with backgrounds in electrical, mechanical, civil and aerospace engineering will find in the book information and inspiration to transfer to their fields of interest the state-of-art in coordination control.