Model variables identification of a gas turbine using a subspace approach based on input/output data measurements

• 作者: Hakim Bagua Ahmed Hafaifa Abdelhamid Iratni Mouloud Guemana
• 来源期刊: 控制理论与技术（英文版）
• 年，卷（期）: 2021,（2）
• 所属期刊栏目: RESEARCH ARTICLES
• 页码范围: 183-196
• 页数: 14页
• 语种: 英文

摘要

This paper deals with a state model identification of a gas turbine used for gas transport,using a subspace approach of the state space model.This method provides a reliable and robust state representation of the model,taking advantage of its benefits in the control,monitoring,and supervision of this machine.The model for each variable is set so that the state matrices associated with the gas turbine model are determined from their real input/output data.The comparison of the obtained identification results with those of the actual turbine operation serves to validate the proposed model in this work.This numerical algorithm of the subspace identification method is full of information and more accurate in terms of residual modeling error,and expresses a very high level of confidence in the identified turbine system dynamics.Hence,the con-trollability and observability tests of turbine operation for different input/output variables allowed to validate the real-time operating stability of the turbine.