Control and Estimation of Distributed Parameter Systems
β Scribed by DESCH, KAPPEL, KUNISCH
- Publisher
- BirkhΓ€user Basel
- Year
- 1991
- Tongue
- English
- Leaves
- 142
- Series
- International Series of Numerical Mathematics
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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 - modeling and control of shells - level set methods - mesh adaptation for parameter estimation problems - shape optimization Advanced graduate students and researchers will find the book an excellent guide to the forefront of control and estimation of distributed parameter systems.
π SIMILAR VOLUMES
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
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
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
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