Litcius/Paper detail

Learning-based symbolic abstractions for nonlinear control systems

Kazumune Hashimoto, Adnane Saoud, Masako Kishida, Toshimitsu Ushio, Dimos V. Dimarogonas

2022Automatica31 citationsDOIOpen Access PDF

Topics & Concepts

Computer scienceSymbolic trajectory evaluationController (irrigation)Nonlinear systemRelation (database)State spaceControl engineeringTrajectoryControl (management)Control systemTheoretical computer scienceArtificial intelligenceModel checkingMathematicsData miningEngineeringBiologyAstronomyPhysicsQuantum mechanicsElectrical engineeringStatisticsAgronomyFormal Methods in VerificationSimulation Techniques and ApplicationsModeling and Simulation Systems
Learning-based symbolic abstractions for nonlinear control systems | Litcius