Reinforcement Learning-Based Backstepping Control for Container Cranes
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-02-19
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
A novel backstepping control scheme based on reinforcement fuzzy Q-learning is proposed for the control of container cranes.
In this control scheme, the modified backstepping controller can handle the underactuated system of a container crane.
Moreover, the gain of the modified backstepping controller is tuned by the reinforcement fuzzy Q-learning mechanism that can automatically search the optimal fuzzy rules to achieve a decrease in the value of the Lyapunov function.
The effectiveness of the applied control scheme was verified by a simulation in Matlab, and the performance was also compared with the conventional sliding mode controller aimed at container cranes.
The simulation results indicated that the used control scheme could achieve satisfactory performance for step-signal tracking with an uncertain lope length.
American Psychological Association (APA)
Sun, Xiao& Xie, Zhihang. 2020. Reinforcement Learning-Based Backstepping Control for Container Cranes. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1193935
Modern Language Association (MLA)
Sun, Xiao& Xie, Zhihang. Reinforcement Learning-Based Backstepping Control for Container Cranes. Mathematical Problems in Engineering No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1193935
American Medical Association (AMA)
Sun, Xiao& Xie, Zhihang. Reinforcement Learning-Based Backstepping Control for Container Cranes. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1193935
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1193935