Decentralized Control and Filtering provides a rigorous framework for examining the analysis, stability and control of large-scale systems, addressing the difficulties that arise because dimensionality, information structure constraints, parametric uncertainty and time-delays. This monograph serves three purposes: it reviews past methods and results from a contemporary perspective; it examines presents trends and approaches and to provide future possibilities; and it investigates robust, reliable and/or resilient decentralized design methods based on a framework of linear matrix inequalities. As well as providing an overview of large-scale systems theories from the past several decades, the author presents key modern concepts and efficient computational methods. Representative numerical examples, end-of-chapter problems, and typical system applications are included, and theoretical developments and practical applications of large-scale dynamical systems are discussed in depth.

This book is devoted to Large Scale Systems methodologies including decomposition, aggregation, and model reduction techniques. The focus is put on theoretical and practical results resulting from the application of these techniques in the area of stability and decentralized control. Every result is illustrated by examples to facilitate understanding. The appendices provide a collection of ready-to-use packages implementing some algorithms included in the book. Graduate students concerned with system and control theory will be interested in this book, since it offers a global synthesis on the problem of structurally constrained control. The book addresses also scientists and lecturers in the areas of large scale systems and control theory.

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Decentralized Control of Complex Systems

A Paradigm for Decentralized Process Modeling presents a novel approach to decentralized process modeling that combines both trends and suggests a paradigm for decentralized PCEs, supporting concerted efforts among geographically-dispersed teams - each local individual or team with its own autonomous process - with emphasis on flexible control over the degree of collaboration versus autonomy provided. A key guideline in this approach is to supply abstraction mechanisms whereby pre-existing processes (or workflows) can be encapsulated and retain security of their internal artifacts and status data, while agreeing with other processes on formal interfaces through which all their interactions are conducted on intentionally shared information. This book is primarily intended to provide an in-depth discussion of decentralized process modeling and enactment technology, covering both high-level concepts and a full-blown realization of these concepts in a concrete system. Either the whole book or selected chapters could be used in a graduate course on software engineering, software process, or software development environments, or even for a course on workflow systems outside computer science (e.g., in a classical engineering department for engineering design, or in a business school for business practices or enterprise-wide management, or in the medical informatics department of a health science institution concerned with computer-assistance for managed care). Selected portions of the book, such as section 2.2 on Marvel, could also be employed as a case study in advanced undergraduate software engineering courses. A Paradigm for Decentralized Process Modeling is a valuable resource for both researchers and practitioners, particularly in software engineering, software development environments, and software process and workflow management, but also in electrical, mechanical, civil and other areas of engineering which have analogous needs for design processes, environmental support and concurrent engineering, and beyond to private and public sector workflow management and control, groupware support, and heterogeneous distributed systems in general.

Decentralized control problems naturally arise in the control of large-scale networked systems. Such systems are regulated by a collection of local controllers in a decentralized manner, in the sense that each local controller is required to specify its control input based on its locally accessible sensor measurements. In this dissertation, we consider the decentralized control of discrete-time, linear systems subject to exogenous disturbances and polyhedral constraints on the state and input trajectories. The underlying system is composed of a finite collection of dynamically coupled subsystems, each of which is assumed to have a dedicated local controller. The decentralization of information is expressed according to sparsity constraints on the sensor measurements that each local controller has access to. In its most general form, the decentralized control problem amounts to an infinite-dimensional nonconvex program that is, in general, computationally intractable. The primary difficulty of the decentralized control problem stems from the potential informational coupling between the controllers. Specifically, in problems with nonclassical information structures, the actions taken by one controller can affect the information acquired by other controllers acting on the system. This gives rise to an incentive for controllers to communicate with each other via the actions that they undertake--the so-called signaling incentive. To complicate matters further, there may be hard constraints coupling the actions and local states being regulated by different controllers that must be jointly enforced with limited communication between the local controllers. In this dissertation, we abandon the search for the optimal decentralized control policy, and resort to approximation methods that enable the tractable calculation of feasible decentralized control policies. We first provide methods for the tractable calculation of decentralized control policies that are affinely parameterized in their measurement history. For problems with partially nested information structures, we show that the optimization over such a policy space admits an equivalent reformulation as a semi-infinite convex program. The optimal solution to these semi-inifinite programs can be calculated through the solution of a finite-dimensional conic program. For problems with nonclassical information structures, however, the optimization over such a policy space amounts to a semi-infinite nonconvex program. With the objective of alleviating the nonconvexity in such problems, we propose an approach to decentralized control design in which the information-coupling states are effectively treated as disturbances whose trajectories are constrained to take values in ellipsoidal "contract" sets whose location, scale, and orientation are jointly optimized with the affine decentralized control policy being used to control the system. The resulting problem is a semidefinite program, whose feasible solutions are guaranteed to be feasible for the original decentralized control design problem. Decentralized control policies that are computed according to such convex optimization methods are, in general, suboptimal. We, therefore, provide a method of bounding the suboptimality of feasible decentralized control policies through an information-based convex relaxation. Specifically, we characterize an expansion of the given information structure, which maximizes the optimal value of the decentralized control design problem associated with the expanded information structure, while guaranteeing that the expanded information structure be partially nested. The resulting decentralized control design problem admits an equivalent reformulation as an infinite-dimensional convex program. We construct a further constraint relaxation of this problem via its partial dualization and a restriction to affine dual control policies, which yields a finite-dimensional conic program whose optimal value is a provable lower bound on the minimum cost of the original decentralized control design problem. Finally, we apply our convexd programming approach to control design to the decentralized control of distributed energy resources in radial power distribution systems. We investigate the problem of designing a fully decentralized disturbance-feedback controller that minimizes the expected cost of serving demand, while guaranteeing the satisfaction of individual resource and distribution system voltage constraints. A direct application of our aforementioned control design methods enables both the calculation of affine controllers and the bounding of their suboptimality through the solution of finite-dimensional conic programs. A case study demonstrates that the decentralized affine controller we compute can perform close to optimal.

The field of database security has expanded greatly, with the rapid development of global inter-networked infrastructure. Databases are no longer stand-alone systems accessible only to internal users of organizations. Today, businesses must allow selective access from different security domains. New data services emerge every day, bringing complex challenges to those whose job is to protect data security. The Internet and the web offer means for collecting and sharing data with unprecedented flexibility and convenience, presenting threats and challenges of their own. This book identifies and addresses these new challenges and more, offering solid advice for practitioners and researchers in industry.