Nonlinear state and parameter estimation of spatially distributed systems

• Tác giả: Felix Sawo
• Ngôn ngữ: eng
• ISBN-13: 978-3866443709
• ISBN: KSP/1000011485
• Ký hiệu phân loại: 621 Applied physics
• Thông tin xuất bản: Karlsruhe : KIT Scientific Publishing, 2009
• Mô tả vật lý: 1 electronic resource (XI, 153 p. p.)
• Bộ sưu tập: Tài liệu truy cập mở
• ID: 223671

Tóm tắt

In this thesis 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 identifying various model parameters. The Covariance Bounds Filter (CBF) allows the efficient estimation of widely distributed systems in a decentralized fashion.