Modeling, Simulation and Control using Python

System modeling deals with the creation of abstract models of system in different forms such as Differential algebraic equations, Block diagram representation, Transfer functions, State space representation, signal flow graph, etc. It is used to present the model so that the dynamics of the model and the flow of signals within is understandable and further control operations can be performed and behavior of the system can be predicted for change in parameters. In this course we deal with discrete models in time domain.

Discrete models in time domain:The model whose operation is not continuous, but discrete for each time steps. Calculation is performed for each time step interval. System model is created by collecting the system data and applying mathematical / physical laws and transforming them into differential equations.

Discrete model contains the amplitude of the output with respect to time. To vary the output of the system, the input to the system can be varied. The branch of mathematics that deals with strategy to select the appropriate input to generate the expected outcome is control theory.

The model to be developed should posses the output as function of input. The function includes all the possible/realistic dynamics. The same model can also be represented in frequency domain which involves amplitude of the output with respect to time.