𝔖 Scriptorium
✦   LIBER   ✦
πŸ“

Control and estimation of distributed parameter systems

✍ Scribed by Wolfgang Desch, Franz Kappel, Karl Kunisch

Publisher
BirkhΓ€user Basel
Year
2003
Tongue
English
Leaves
280
Series
Austria, July 15-21, 2001
Edition
1
Category
Library
⬇  Acquire This Volume

No coin nor oath required. For personal study only.

πŸ“œ SIMILAR VOLUMES

Control and Estimation of Distributed Pa
πŸ“ Control and Estimation of Distributed Parameter Systems
✍ DESCH, KAPPEL, KUNISCH πŸ“‚ Library πŸ“… 1991 πŸ› BirkhΓ€user Basel 🌐 English

Consisting of 16 refereed original contributions, this volume presents a diversified collection of recent results in control of distributed parameter systems. Topics addressed include - optimal control in fluid mechanics - numerical methods for optimal control of partial differential equations - mod

Control and estimation in distributed pa
πŸ“ Control and estimation in distributed parameter systems
✍ H. T. Banks πŸ“‚ Library πŸ“… 1987 πŸ› Society for Industrial and Applied Mathematics 🌐 English

Research in control and estimation of distributed parameter systems encompasses a wide range of applications including both fundamental science and emerging technologies. These expository papers provide substantial stimulus to both young researchers and experienced investigators in control theory. T

Control and Estimation in Distributed Pa
πŸ“ Control and Estimation in Distributed Parameter Systems
✍ H. T. Banks πŸ“‚ Library πŸ“… 1987 πŸ› Society for Industrial Mathematics 🌐 English

Research in control and estimation of distributed parameter systems encompasses a wide range of applications including both fundamental science and emerging technologies. These expository papers provide substantial stimulus to both young researchers and experienced investigators in control theory. T

Nonlinear state and parameter estimation
πŸ“ Nonlinear state and parameter estimation of spatially distributed systems
✍ Sawo F. πŸ“‚ Library πŸ“… 2009 πŸ› Univer. Karlsruhe 🌐 English

In this book two probabilistic model-based estimators are introduced that allow the reconstruction and identification of space-time continuous physical systems. The Sliced Gaussian Mixture Filter (SGMF) exploits linear substructures in mixed linear/nonlinear systems, and thus is well-suited for iden

Nonlinear state and parameter estimation
πŸ“ Nonlinear state and parameter estimation of spatially distributed systems
✍ Felix Sawo πŸ“‚ Library πŸ“… 2009 πŸ› Kit Scientific Publishing 🌐 English

In this book two probabilistic model-based estimators are introduced that allow the reconstruction and identification of space-time continuous physical systems. The Sliced Gaussian Mixture Filter (SGMF) exploits linear substructures in mixed linear/nonlinear systems, and thus is well-suited for iden