Adaptive Dynamic Programming: Solltrajektorienfolgeregelung und Konvergenzbedingungen

• Autor principal: Köpf, Florian (auth)
• Format: Electrònic Capítol de llibre
• Publicat: KIT Scientific Publishing 2022
• Col·lecció: Karlsruher Beiträge zur Regelungs- und Steuerungstechnik
• Matèries: Electrical engineering; Adaptive Dynamic Programming (ADP); Reinforcement Learning (RL); Persistent Excitation (PE); adaptive Optimalregelung; lernende Regler; KI; Adaptive Optimal Control; Learning-Based Control; AI
• Accés en línia: DOAB: download the publication; DOAB: description of the publication

Sumari

In this work, discrete-time and continuous-time methods that integrate flexible reference trajectory representations into Adaptive Dynamic Programming approaches are presented and analyzed for the first time. Moreover, theoretical conditions on the system state are derived that ensure the persistent excitation property, which is crucial for the convergence of the adaptation. Real-world applications of the presented adaptive optimal trajectory tracking control methods reveal their potential.

Descripció física

1 electronic resource (304 p.)

ISBN

KSP/1000145970

Accés

Open Access