Rautenberg, Carlos Nicolas2014-03-142014-03-142010-03-31etd-04212010-100919http://hdl.handle.net/10919/27103In this thesis we develop a rigorous mathematical framework for analyzing and approximating optimal sensor placement problems for distributed parameter systems and apply these results to PDE problems defined by the convection-diffusion equations. The mathematical problem is formulated as a distributed parameter optimal control problem with integral Riccati equations as constraints. In order to prove existence of the optimal sensor network and to construct a framework in which to develop rigorous numerical integration of the Riccati equations, we develop a theory based on Bochner integrable solutions of the Riccati equations. In particular, we focus on ℐ<sub>p</sub>-valued continuous solutions of the Bochner integral Riccati equation. We give new results concerning the smoothing effect achieved by multiplying a general strongly continuous mapping by operators in ℐ<sub>p</sub>. These smoothing results are essential to the proofs of the existence of Bochner integrable solutions of the Riccati integral equations. We also establish that multiplication of continuous ℐ<sub>p</sub>-valued functions improves convergence properties of strongly continuous approximating mappings and specifically approximating C₀-semigroups. We develop a Galerkin type numerical scheme for approximating the solutions of the integral Riccati equation and prove convergence of the approximating solutions in the ℐ<sub>p</sub>-norm. Numerical examples are given to illustrate the theory.In CopyrightRiccati EquationKalman FilterMobile Sensor NetworksOptimal FilteringA Distributed Parameter Approach to Optimal Filtering and Estimation with Mobile Sensor NetworksDissertationhttp://scholar.lib.vt.edu/theses/available/etd-04212010-100919/