What is the difference between nominal model and mathematical model of a real plant?
I am interested in understanding the difference since I want to understand why in some cases is not the best idea to proceed with the control design based on the model.
This might give you an idea of what is the nominal model, and what it does.
"In continuous control problems we always have models. The idea that we are going to build a self-driving car from trial and error is ludicrous. Fitting models, while laborious, is not out of the realm of possibilities for most systems of interest. Moreover, often times a coarse model suffices in order to plan a nearly optimal control strategy. How much can a model improve performance even when the parameters are unknown or the model doesn’t fully capture all of the system’s behavior?
In this post, I’m going to look at one of the simplest uses of a model in reinforcement learning. The strategy will be to estimate a predictive model for the dynamical process and then to use it in a dynamic programming solution to the prescribed control problem. Building a control system as if this estimated model were true is called nominal control, and the estimated model is called the nominal model. Nominal control will serve as a useful baseline algorithm for the rest of this series.
From the above, you can see the difference between a nominal model (predictive) and a mathematical model (exact).
This paper address the mathematical model https://www.pearsonhighered.com/assets/samplechapter/0/1/3/6/0136156738.pdf
