Modeling and Identification of Time-Varying Systems from Noisy Observations.

Abstract

The modeling and identification of a rather large class of nonlinear time-varying systems is discussed. A general model for such systems is given, and the subsequent identification problem is formulated in terms of a parameter estimation problem. Random as well as unknown but bounded variations in the parameters are considered, and recursive estimation algorithms are stated in both cases. A definition of the concept of a system being slowly varying is given, and conditions are presented under which a system is slowly varying.

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1975
Accession Number
ADA013064

Entities

People

  • Philip H. Fiske

Organizations

  • University of Michigan

Tags

DTIC Thesaurus Topics

  • Acquisition
  • Algorithms
  • Identification
  • Observation

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms