Parameter estimation in nonlinear distributed systems-approximation theory and convergence results

Approximation Results for Parameter Estimation

In this paper we present an approximation framework and theoretical convergence results for a class of parameter estimation problems for general abstract nonlinear hyperbolic systems. These systems include as a special case those modeling a large class of nonlinear elastomers.

Distributed Statistical Estimation and Rates of Convergence in Normal Approximation

This paper presents new algorithms for distributed statistical estimation that can take advantage of the divide-and-conquer approach. We show that one of the key benefits attained by an appropriate divide-and-conquer strategy is robustness, an important characteristic of large distributed systems. We introduce a class of algorithms that are based on the properties of the geometric median, estab...

a Simplified Model of Distributed Parameter Systems

A generalized simplified model for describing the dynamic behavior of distributed parameter systems is proposed. The various specific characteristics of gain and phase angle of distributed parameter systems are investigated from frequency response formulation and complex plane representation of the proposed simplified model. The complex plane investigation renders some important inequality cons...

State and Parameter Estimation for Nonlinear Systems

A constructive method is proposed for the design of nonlinear adaptive observers with global convergence for recursive joint estimation of states and parameters. It extends an earlier result to systems with a more general parametrization. The considered nonlinear systems are those typically considered for the design of high gain observers with additional terms involving unknown parameters. A nu...

Elimination Theory for Nonlinear Parameter Estimation