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Annotation. Proceedings from the First International Conference on Inverse Problems, Recent Theoretical Development and Numerical Approaches, held at the City University of Hong Kong from January 9-12, 2002.
The articles in this volume cover recent work in the area of flow control from the point of view of both engineers and mathematicians. These writings are especially timely, as they coincide with the emergence of the role of mathematics and systematic engineering analysis in flow control and optimization. Recently this role has significantly expanded to the point where now sophisticated mathematical and computational tools are being increasingly applied to the control and optimization of fluid flows. These articles document some important work that has gone on to influence the practical, everyday design of flows; moreover, they represent the state of the art in the formulation, analysis, and computation of flow control problems. This volume will be of interest to both applied mathematicians and to engineers.
The third Conference on Computation and Control was held at Mon tana State University in Bozeman, Montana from August 5-11, 1992 and this proceedings represents the evolution that the conference has taken since its 1988 and 1990 predecessors. The first conference and proceedings (Volume 1 in PSCT) nurtured a dialogue between researchers in control theory and the area of numerical computation. This cross-fertilization was continued with the 1990 conference and proceedings (Volume 11 in PSCT) while forecasting the theme for this conference. The present volume contains a collection of papers addressing issues ranging from noise abatement via smart material technology, robotic vi sion, and param...
This book describes several novel applications currently under investigation that exploit the unique actuator and sensor capabilities of smart material compounds. In addition to present and projected applications, this book provides comprehensive coverage of both linear and nonlinear modeling techniques necessary to characterize materials in a manner that facilitates transducer design and control development. The author focuses on ferroelectric, magnetic, and shape memory compounds and also addresses applications exploiting amorphous and ionic polymers, magnetorheological compounds, and fiber optic sensors. By providing a unified treatment of both linear and nonlinear characterization frameworks, Smart Material Systems: Model Development encompasses both low to moderate drive levels, which constitute the primary focus of most present texts, and the high drive regimes dictated by present and future applications. This will significantly enhance the design of transducers and control systems which exploit the unique actuator and sensor capabilities provided by smart material compounds.
This volume contains a collection of papers delivered by the partici pants at the second Conference on Computation and Control held at Mon tana State University in Bozeman, Montana from August 1-7, 1990. The conference, as well as this proceedings, attests to the vitality and cohesion between the control theorist and the numerical analyst that was adver tised by the first Conference on Computation and Control in 1988. The proceedings of that initial conference was published by Birkhiiuser Boston as the first volume of this same series entitled Computation and Control, Proceedings of the Bozeman Conference, Bozeman, Montana, 1988. Control theory and numerical analysis are both, by their very ...
Provides comprehensive coverage of the most recent developments in the theory of non-Archimedean pseudo-differential equations and its application to stochastics and mathematical physics--offering current methods of construction for stochastic processes in the field of p-adic numbers and related structures. Develops a new theory for parabolic equations over non-Archimedean fields in relation to Markov processes.
Many mathematical models of physical, biological and social systems involve partial differential equations (PDEs). The desire to understand and influence these systems naturally leads to considering problems of control and optimization. This book presents important topics in the areas of control of PDEs and of PDE-constrained optimization, covering the full spectrum from analysis to numerical realization and applications. Leading scientists address current topics such as non-smooth optimization, Hamilton–Jacobi–Bellmann equations, issues in optimization and control of stochastic partial differential equations, reduced-order models and domain decomposition, discretization error estimates for optimal control problems, and control of quantum-dynamical systems. These contributions originate from the “International Workshop on Control and Optimization of PDEs” in Mariatrost in October 2011. This book is an excellent resource for students and researchers in control or optimization of differential equations. Readers interested in theory or in numerical algorithms will find this book equally useful.
Interest in the area of control of systems defined by partial differential Equations has increased strongly in recent years. A major reason has been the requirement of these systems for sensible continuum mechanical modelling and optimization or control techniques which account for typical physical phenomena. Particular examples of problems on which substantial progress has been made are the control and stabilization of mechatronic structures, the control of growth of thin films and crystals, the control of Laser and semi-conductor devices, and shape optimization problems for turbomachine blades, shells, smart materials and microdiffractive optics. This volume contains original articles by w...
This volume synthesizes theoretical and practical aspects of both the mathematical and life science viewpoints needed for modeling of the cardiovascular-respiratory system specifically and physiological systems generally. Theoretical points include model design, model complexity and validation in the light of available data, as well as control theory approaches to feedback delay and Kalman filter applications to parameter identification. State of the art approaches using parameter sensitivity are discussed for enhancing model identifiability through joint analysis of model structure and data. Practical examples illustrate model development at various levels of complexity based on given physiological information. The sensitivity-based approaches for examining model identifiability are illustrated by means of specific modeling examples. The themes presented address the current problem of patient-specific model adaptation in the clinical setting, where data is typically limited.