A data-driven switching control approach for braking systems with constraints

DOI10.1016/j.nahs.2022.101220zbMath1500.93031OpenAlexW4281625584MaRDI QIDQ2085140

Sergio M. Savaresi, Simone Formentin, Valentina Breschi, Andrea Sassella

Publication date: 14 October 2022

Published in: Nonlinear Analysis. Hybrid Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.nahs.2022.101220

zbMATH Keywords

switching controldata-driven controlreference governorsbraking controlhybrid model predictive control

Mathematics Subject Classification ID

Application models in control theory (93C95) Control/observation systems governed by functional relations other than differential equations (such as hybrid and switching systems) (93C30) Model predictive control (93B45)

Uses Software

• HYSDEL
• Hybrid Toolbox

Cites Work

• Active braking control systems design for vehicles
• Direct learning of LPV controllers from data
• Control of systems integrating logic, dynamics, and constraints
• Virtual reference feedback tuning: A direct method for the design of feedback controllers
• Piecewise affine regression via recursive multiple least squares and multicategory discrimination
• Direct data‐driven design of switching controllers

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