Identification and Control of Linear Stochastic Systems Using Spline Functions.

Abstract

The report discusses parameter identification and adaptive control of linear plants excited by white, Gaussian noise, the linear observations being made in the presence of additive white, Gaussian noise. The Bayesian approach is taken throughout this study. As this approach leads to identification and control schemes which cannot be implemented exactly, the spline functions are used to approximate these schemes very closely. These approximations are studied in detail and their performance is demonstrated by means of several examples.

Document Details

Document Type
Technical Report
Publication Date
May 01, 1973
Accession Number
AD0766920

Entities

People

  • Demetrios G. Lainiotis
  • Jayant G. Deshpande

Organizations

  • University of Texas at Austin

Tags

DTIC Thesaurus Topics

  • Additives (Chemicals)
  • Bayesian Networks
  • Gaussian Noise
  • Identification
  • Noise
  • Observation

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)

Technology Areas

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