Affordable Access

Publisher Website

Statistical identification for optimal control of supercritical thermal power plants

Authors
Journal
Automatica
0005-1098
Publisher
Elsevier
Publication Date
Volume
17
Issue
1
Identifiers
DOI: 10.1016/0005-1098(81)90090-x
Keywords
  • Section 2. Identification Application (A) Identification Of Technical System
Disciplines
  • Design

Abstract

Abstract The use of a multivariate autoregressive model for the implementation of a new practical optimal control of a supercritical thermal power plant is discussed. The control is realized by identifying the system characteristics of the plant under the conventional PID control by the autoregressive model fitting and then implementing the digital control to correct the defect of the analog control. The procedure of identification and the controller implementation is described in detail by using the experimental results of a real plant. The results clearly demonstrate the advantage of the new controller over the conventional PID controller. The experience of the commercial operation of the plant confirms that the new controller is extremely robust against the gradual change of the plant characteristics, and this shows the practical utility of the identification procedure on which the design of the controller is based.

There are no comments yet on this publication. Be the first to share your thoughts.