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In this unified account of the mathematical theory of distributed parameter systems (DPS), the authors cover all major aspects of the control, estimation, and identification of such systems, and their application in engineering problems. The first part of the book is devoted to the basic results in deterministic and stochastic partial differential equations, which are applied to the optimal control and estimation theories for DPS. Part two then applies this knowledge in an engineering setting, discussing optimal estimators, optimal sensor and actuator locations, and computational techniques.
This text investigates the mathematical framework and practical application of control, estimation, and identification within distributed parameter systems. John H. Seinfeld and Sigeru Omatu provide a rigorous synthesis of deterministic and stochastic partial differential equations to address complex engineering challenges. The authors establish a foundational methodology for optimizing system performance through advanced computational techniques and theoretical modeling.
What You Will Find
Experts recognize this volume as a foundational reference for researchers and engineers working in the field of control theory. Readers frequently note the high level of mathematical density and the technical rigor required to fully engage with the presented proofs and applications.
Page Count:
448
Publication Date:
1989-09-14
Publisher:
Oxford University Press
ISBN-10:
0198532954
ISBN-13:
9780198532958
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