Thesis

New modelling and control methods with application to combined cycle power plants

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Awarding institution
  • University of Strathclyde
Date of award
  • 2002
Thesis identifier
  • T10505
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Abstract
  • This thesis reports the analysis and modelling required to build a software simulation of combine cycle power plants. A new MIMO PID controller tuning method and a novel predictive PID controller design method for MIMO systems are also described in the thesis. The emphasis of this work is on simulation; identification and controller design methods. The thesis begins with an account of the combined cycle power plant modelling and simulation development. This culminates in a library of different blocks and subsystems of combined cycle power plants. The simulation development shows how the steady state and dynamic behaviour of combined cycle power plants can be simulated and implemented in the SMULINK and MATLAB environment using per unit models, which are suitable for control design. In the identification stage, the relay identification method is used to identify the critical points of the system for a newly defined criterion at bandwidth frequency. Then, the identified critical points are used to tune PID controllers. The thesis then outlines multivariable PID tuning methods and makes a comparison between these methods and the new relay identification method concerning their robustness for MIMO systems. The last two chapter of thesis are concerned with a new predictive PID controller design method for both SISO and MIMO systems. This methodology is concerned with the design of PID controllers, which have similar features to the model-based predictive controller. Generalized Predictive Control (GPC) design principles are used to develop the PID control with predictive capabilities for both SISO and MIMO systems. The combined cycle power plant simulation, especially the boiler subsystem, is used as an example throughout the thesis.
Resource Type
DOI
EThOS ID
  • uk.bl.ethos.248795
Date Created
  • 2002
Former identifier
  • 638691

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