JOURNAL ARTICLE

Adaptive fuzzy finite‐time formation asymptotic tracking control for nonholonomic multirobot systems with inputs quantization

Shijie DongYongming Li

Year: 2023 Journal:   International Journal of Adaptive Control and Signal Processing Vol: 37 (11)Pages: 2875-2894   Publisher: Wiley

Abstract

Summary This paper investigates the finite‐time formation tracking control problem for nonholonomic multirobot systems with inputs quantization. The fuzzy logic systems (FLSs) and adaptive method are introduced to approximate unknown nonlinear functions and parameters. Multirobot needs to keep safe and effective communicating range, the barrier function and prescribed performance method are employed to ensure collision avoidance and connectivity maintenance. Then, in order to make each robot more precisely and quickly track referenced leader's trajectory and consider the finite channel bandwidth in practical applications, the travel range of robots can be maintained at more secure region and formation can operate normally within the given bandwidth. By combining the command filter and finite‐time theory, a novel decentralized finite‐time formation asymptotic tracking (FTFAT) control strategy is further proposed based on inputs quantization technology, it guarantees that all signals are bounded and the formation tracking errors asymptotically converge to zero in finite‐time. Finally, the practicability of FTFAT strategy is demonstrated absolutely for nonholonomic multirobot systems.

Keywords:
Nonholonomic system Control theory (sociology) Quantization (signal processing) Computer science Bounded function Nonlinear system Fuzzy logic Mobile robot Robot Mathematics Artificial intelligence Algorithm Control (management)

Metrics

2
Cited By
0.88
FWCI (Field Weighted Citation Impact)
31
Refs
0.61
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Distributed Control Multi-Agent Systems
Physical Sciences →  Computer Science →  Computer Networks and Communications
Control and Dynamics of Mobile Robots
Physical Sciences →  Engineering →  Control and Systems Engineering
Adaptive Control of Nonlinear Systems
Physical Sciences →  Engineering →  Control and Systems Engineering

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