swMATH ID: 31382
Software Authors: Emerson Boeira; Diego Eckhard
Description: pyvrft: A Python package for the Virtual Reference Feedback Tuning, a direct data-driven control method. In this paper, the pyvrft, a Python package for the data-driven control method known as Virtual Reference Feedback Tuning (VRFT), is presented. Virtual Reference Feedback Tuning is a control design technique that does not use a mathematical model from the process to be controlled. Instead, it uses input and output data from an experiment to compute the controller’s parameters, aiming to minimize an Model Reference criterion. The package implements an unbiased estimate of the controller for MIMO (Multiple-Input Multiple-Output) processes using both least-squares and instrumental variable techniques. The package also provides accessory functions to import data and to perform MIMO systems simulations, together with some examples.
Homepage: https://www.sciencedirect.com/science/article/pii/S2352711019302894
Source Code: https://github.com/datadrivencontrol/pyvrft
Dependencies: Python
Keywords: SoftwareX publication; Control systems; Data-driven control; VRFT; Python; Virtual Reference Feedback Tuning
Related Software: SciPy; Python; System Identification Toolbox; pyphysio; eadf; R; Matlab; impulseest; VRFT; Matplotlib; NumPy
Cited in: 0 Publications

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