A Recursive Estimation Algorithm for Discrete-Time Systems with Unknown Noise Parameters.

Abstract

The purpose of this report is to develop a recursive algorithm for state estimation for systems with uncertain models. The algorithm uses a combined detection-estimation scheme whereby the set in which the uncertainties are contained is detected, and appropriate estimator is then used. The approach used is an extension of a weighted minimax performance criteria to the dynamic case. Since global optimal solution is not possible, an approximate algorithm is derived which only optimizes the stage-by-stage performance without changing any past decisions. The expressions for the algorithm and an approximation of its performance are derived. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1978
Accession Number
ADA069794

Entities

People

  • Nathan Guedalia

Organizations

  • University of Illinois Urbana–Champaign

Tags

Communities of Interest

  • C4I
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Asymptotic Series
  • Bessel Functions
  • Computations
  • Covariance
  • Detection
  • Detectors
  • Electrical Engineering
  • Engineering
  • Estimators
  • Filters
  • Illinois
  • Mathematical Filters
  • Probability
  • Random Variables
  • Security
  • Universities

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.