MODELS FOR PREDICTION AND CONTROL IX DYNAMIC MODELS.

Abstract

In previous chapters we have considered the problem of representing practically occurring time series by linear stochastic difference equations. As a first example of the use of such models we have shown how they may be used for forecasting both non-seasonal and seasonal series. These series may also be used to represent disturbances such as arise in economics, engineering and in business applications. To control such systems we need not only an adequate disturbance model, but also a dynamic model which can take account of the various types of inertia which may be inherent in the process. The present chapter provides an introduction to models based on difference equations which give a parsimonious mathematical representation of the dynamic behaviour of physical systems. Two cases will be distinguished: (1) When the input to the system is kept fixed over constant intervals of time as in the discrete control systems, and, (2) When an essentially continuous input and output are sampled at equidistant time intervals and the resulting discrete time series used to estimate the dynamic response or transfer function of the system.

Document Details

Document Type
Technical Report
Publication Date
May 01, 1967
Accession Number
AD0656684

Entities

People

  • G. M. Jenkins
  • George E. P. Box

Organizations

  • University of Wisconsin–Madison

Tags

DTIC Thesaurus Topics

  • Commerce
  • Control Systems
  • Delphi Method
  • Difference Equations
  • Dynamic Response
  • Economics
  • Engineering
  • Equations
  • Intervals
  • Mathematical Analysis
  • Mathematics
  • Production Engineering
  • Systems Engineering
  • Time Intervals
  • Transfer Functions

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Computational Modeling and Simulation
  • Control Systems Engineering.