Overview

D-FPD is a numerical/discrete version of FPD to tackle both discrete and continuous data-driven control problems. D-FPD can be used to compute policies from examples for constrained, possibly stochastic/nonlinear, systems.

Download

• To download and run the software, please refer to the public GitHub repository.

Prerequisites

• MATLAB.

Changelog

• Please refer to the public GitHub repository for the software history.

References, more information, and resources

• E. Ferrentino, P. Chiacchio and G. Russo, "Discrete fully probabilistic design: towards a control pipeline for the synthesis of policies from examples," 2023 31st Mediterranean Conference on Control and Automation (MED), Limassol, Cyprus, 2023, pp. 759-764, DOI: 10.1109/MED59994.2023.10185706.
• D. Gagliardi and G. Russo, "On a probabilistic approach to synthesize control policies from example datasets" Automatica vol. 137, n. 110121, 2022, DOI: 10.1016/j.automatica.2021.110121.