Optimal measurement methods for distributed parameter system identification
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Optimal measurement methods for distributed parameter system identification by Dariusz UciЕ„ski

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Published by CRC Press in Boca Raton, Fla .
Written in English

Subjects:

  • Distributed parameter systems,
  • Mathematical optimization,
  • System analysis,
  • Control theory

Book details:

Edition Notes

Includes bibliographical references (p. 339-365) and index

StatementDariusz Uciński
SeriesSystems and control series, Taylor & Francis systems and control book series
Classifications
LC ClassificationsQA402 .U35 2005
The Physical Object
Paginationxvii, 371 p. :
Number of Pages371
ID Numbers
Open LibraryOL17135530M
ISBN 100849323134
LC Control Number2004054473

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  Optimal Measurement Methods for Distributed Parameter System Identification Pages pages For dynamic distributed systems modeled by partial differential equations, existing methods of sensor location in parameter estimation experiments are either limited to one-dimensional spatial domains or require large investments in software by: Optimal measurement methods for distributed parameter system identification. [Dariusz Uciński] -- "Unique in its focus, this book outlines optimal sensor placement strategies for parameter identification in dynamic distributed systems modeled by partial differential equations. Optimal Measurement Methods for Distributed Parameter System Identification discusses the characteristic features of the sensor placement problem, . "Optimal Measurement Methods for Distributed Parameter System Identification" discusses the characteristic features of the sensor placement problem, analyzes classical and recent approaches, and proposes a wide range of original solutions, culminating in the most comprehensive and timely treatment of the issue available.

Save on Optimal Measurement Methods for Distributed Parameter System Identification by Dariusz Ucinski. Shop your textbooks from Zookal AU today. For dynamic distributed systems modeled by partial differential equations, existing methods of sensor location in parameter estimation experiments are either limited to one-dimensional spatial domains. The book covers topics of distributed parameter control systems in the areas of simulation, identification, state estimation, stability, control (optimal, stochastic, and coordinated), numerical approximation methods, optimal sensor, and actuator positioning. Abstract: The problem of optimal measurement locations for state estimation in linear distributed parameter systems is considered. It has previously been shown that the optimal sensor location problem for distributed systems can be posed as an optimal control problem for a system described by the infinite-dimensional matrix Riccati equation for the filter covariance. In control theory, a distributed parameter system (as opposed to a lumped parameter system) is a system whose state space is systems are therefore also known as infinite-dimensional systems. Typical examples are systems described by partial differential equations or by delay differential equations.

Optimal measurement methods for distributed parameter system identification. [Dariusz Uciński] -- Ucinski (U. of Zielona G ra, Poland) offers an account of classical and recent work on sensor placement for parameter estimation in dynamic distributed systems modeled by partial differential. Control of distributed parameter systems (DPS) remains a challenging task, as the system dynamics are infinite-dimensional. Model reduction of such systems may produce instabilities and thus it is essential that the model reduction methodology used is robust. Different orthogonal functions are optimal for different parameter probability. As a matter of fact the control theory of distributed parameter systems covers a very large and diverse area of problems and methods and the study of some specific problems arising in applications represents much of the substance of the theory. Optimal Design Techniques for Distributed Parameter Systems H.T. Banksy D. Rubioz N. Saintierx M.I. Troparevsky{Abstract A wide number of inverse problems consist in select-ing best parameter values of a given mathematical model based ts to measured data. These are usu-ally formulated as optimization problems and the.