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A "hybrid" physical model controller based on a screen and a series of sensors.
The benzene toluene system for ITCDIC is studied as illustration, where WGMC is compared with another generic model controller based on a data-driven model (TGMC) and an internal model controller (IMC).
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The IMC (Internal Model Control) controller based on robust tuning can improve the robustness and dynamic performance of the system.
In the paper, a model predictive controller based on reduced order model is proposed to control belt conveyor system, which is an electro-mechanics complex system with long visco-elastic body.
The proposed strategy consists in designing a robust nonlinear model predictive controller based on a minimal nonlinear model.
A methodology is proposed for designing a robust nonlinear model predictive controller based on a Volterra series model with uncertain coefficients.
Real-time control is also achievable with model predictive controller based on convex formulation.
The design of the nonlinear model predictive controller consists of two steps: the first step is to design a linear model predictive controller based on the linear part of the system at each sample instant, then an overall convergent nonlinear part is added to the linear model predictive controller to combine a nonlinear controller using error driven.
The design of a Model Predictive Controller based on economic objectives is discussed, and is used to control the variables typically under manual control.
We design a model predictive controller based on measurements of the actual train positions.
This paper presents the design of a one step ahead model predictive controller based on a neural network for a single input single output nonlinear system.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com