Reduced-parameter fractional-order modeling of large dynamical system: Application to Gas Turbine

Nowadays, gas turbines are popularly used for power generation. Widespread installations and the dynamic nature of this system has increased the necessity of its accurate modeling and control. It is a large and complex dynamical system and exact identification of its parameters like temperature and speed are the important issues. Noticeable research activities are going on so far in this field in order to understand and simplify the nonlinear behavior of these complex systems. However, the need for simple and compact models has been a strong motivation for researchers. Most of the advanced controllers are model based, if model is bulky or having large parameter then controller design become tedious and time consuming. Online implementation of such model driven strategy is also the main concern. Further it results in sluggish operation and also deteriorates the closed loop performance. Hence simplified and compact model is an important requirement. This paper proposes, application of fractional calculus theory to find compact model of gas turbine. A simple and compact fractional-order models are obtained using parameter reduction technique. A local optimization problem is posed to represent large parameter integer-order systems by few parameters fractional-order models. The dynamics of original system are retained in compact fractional-order models because of its memory type nature. Results shows that the proposed models completely represent the dynamic of large parameter integer-order system.