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Künstliche Neuronale Netzwerke Zur Adaptiven Fahrdynamikregelung
Paperback
Series: Autouni - Schriftenreihe, Book 171
ISBN13: 9783658431082
Publisher: Springer Vieweg
Published: Jan 5 2024
Pages: 283
Weight: 0.85
Height: 0.68 Width: 5.83 Depth: 8.27
Language: German
In dem vorliegenden Buch wird der Einsatz eines hybriden Regelungskonzeptes für die Fahrdynamikregelung eines autonomen Versuchsträgers untersucht. Dabei wird ein modellbasierter, kaskadierter Querdynamikregler um ein künstliches neuronales Netzwerk (KNN) erweitert. Das KNN wird ohne Vorwissen implementiert und aktiv im geschlossenen Regelkreis trainiert. Die Untersuchungen werden dabei sowohl in Simulationen, als auch in einem realen Versuchsträger durchgeführt. Die Versuche zeigen das Leistungsvermögen des hybriden Regelungskonzeptes. Bei geringer Fahrzeugdynamik ist eine präzise Fahrzeugführung auch ohne KNN möglich. Bei hoher Dynamik resultieren jedoch Abweichungen vom Sollkurs, die durch das iterativ lernende Netzwerk schrittweise reduziert werden. Durch die situationsabhängige Optimierung der Netzwerkgewichte wird der Einfluss des systematischen Fehlers des zu Grunde liegenden Modells kompensiert und die Regelgüte verbessert. Dieses Verhalten kann durch geeignete Auswahl derDesignparameter des KNN für jedes der betrachteten Szenarien aufgezeigt werden. Die Anpassung der Netzwerkgewichte ermöglicht sowohl im Fehlerfall als auch bei hoher Fahrzeugdynamik und ungenauer Systemidentifikation eine Verbesserung der Regelgüte im Vergleich zum rein modellbasierten Basisregler.
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