Adaptive Dynamic Programming: Solltrajektorienfolgeregelung und Konvergenzbedingungen
Abstract
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.
Keywords
Adaptive Dynamic Programming (ADP); Reinforcement Learning (RL); Persistent Excitation (PE); adaptive Optimalregelung; lernende Regler; KI; Adaptive Optimal Control; Learning-Based Control; AIDOI
10.5445/KSP/1000145970ISBN
9783731511939Publisher
KIT Scientific PublishingPublisher website
https://www.ksp.kit.edu/index.php?link=shop&sort=allPublication date and place
2022Series
Karlsruher Beiträge zur Regelungs- und Steuerungstechnik, 18Classification
Electrical engineering