Accession Number:

AD0626856

Title:

A DISCRETE PREDICTOR CONTROLLER APPLIED TO SINUSOIDAL PERTURBATION ADAPTIVE OPTIMIZATION.

Descriptive Note:

Technical rept.,

Corporate Author:

WISCONSIN UNIV MADISON DEPT OF STATISTICS

Report Date:

1965-11-01

Pagination or Media Count:

29.0

Abstract:

Uncontrollable and unmeasurable disturbances possessing nonstationary characteristics often create major control problems in chemical processes. Typical of these fluctuations are composition changes in a homogeneous system and catalyst activity changes in a heterogeneous system. In this report, Box and Jenkins theory of discrete predictive control is mechanized on an analog computer and applied to sinusoidal perturbation adaptive optimization of a natural gas combustion system. Process dynamics and the stochastic characteristics of disturbances are programmed into the discrete predictor controller to provide an adaptive control system which allows for process upsets before they occur. Statistically designed experiments are constructed to evaluate the performance. An outline of the theory and a description of the equipment is presented. Results show that the insertion of the discrete predictor controller into the adaptive control loop provides significant improvement over the conventional proportional feedback of sinusoidal adaptive optimization. Author

Subject Categories:

  • Industrial Chemistry and Chemical Processing
  • Statistics and Probability
  • Combustion and Ignition

Distribution Statement:

APPROVED FOR PUBLIC RELEASE