Iterative Learning Control Based Robust Distributed Algorithm for Non-Holonomic Mobile Robots Formation

This paper presents an iterative learning control-based robust distributed algorithm on the formation issue for a group of differential-drive mobile robots. The fundamental robustness problem in practical application involving initial state shifts, disturbances, noises, and communication time-delays...

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Veröffentlicht in:IEEE Access Jg. 6; S. 61904 - 61917
Hauptverfasser: Sun, Shihao, Endo, Takahiro, Matsuno, Fumitoshi
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Piscataway IEEE 2018
Institute of Electrical and Electronics Engineers (IEEE)
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Delays
differential-drive mobile robots
Dimensional analysis
Distributed algorithms
Electrical engineering. Electronics. Nuclear engineering
Iterative learning control
Iterative methods
Machine learning
Mathematical analysis
Mobile robots
Multi-robot systems
Robots
Robust control
robust formation control
Task analysis
TK1-9971
Trajectory
Two dimensional analysis
ISSN:2169-3536, 2169-3536
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Zusammenfassung:This paper presents an iterative learning control-based robust distributed algorithm on the formation issue for a group of differential-drive mobile robots. The fundamental robustness problem in practical application involving initial state shifts, disturbances, noises, and communication time-delays are considered. The distributed algorithm is proposed for each robot in directed network, which is based on the iterative learning rule with both predictive and current learning terms. It is shown that the convergence of formation tracking objective can be guaranteed under a matrix norm condition by using the two-dimensional analysis approach. Numerical simulation and experiment are both given to validate the effectiveness of the proposed algorithm.
Bibliographie:ObjectType-Article-1
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2018.2876545