With rising complexities in control algorithms for systems like gas turbine engine, a good dynamic model is necessary for validating the algorithm. There are multiple ways in which the dynamic models can be developed.  White-box modelling approaches rely on energy and thermodynamic balance equations.

Hence, assumptions and linearization methods are required to simplify and solve complex dynamics. Models and control systems designed using simplified linearized equations are not accurate enough to capture system dynamics precisely.

In this presentation, you will learn how to make use of data from the gas turbine system to model the dynamics of the system with better accuracy using a neural network and deep learning method.