Project Abstract
Because of the high demand of the electricity market, the power producers are eager to continuously investigate new methods of optimization for design, manufacturing, control and maintenance of Industrial Power Plant Gas Turbines (IPGTs). New IPGTs are equipped with modern control systems delivering data to the control room through a number of required sensors. Various data-processing methods have been proposed or developed for an array of tasks such as modelling, simulation, diagnosis, sensor validation and condition monitoring, but have limitations such as inaccuracy and being unreliable because of high non-linearity in IPGTs. Artificial Neural Networks (ANNs) have been regarded as suitable and powerful tools for data processing and modelling of non-linear systems. The proposed research project will focus on analysis, modelling, and control of Industrial Power Plant Gas Turbines (IPGTs) using ANNs. It aims to develop: (i) a methodology for analyzing and designing a robust adaptive neural control system for