Adaptive Fuzzy Control for Multi-Agent Systems With Unknown Measurement Sensitivity via a Simplified Backstepping Approach
- Authors
- Du, Zhixu; Liang, Hongjing; Ahn, Choon Ki
- Issue Date
- 6월-2022
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Sensitivity; Backstepping; Current measurement; Gain measurement; Adaptive control; Protocols; Multi-agent systems; Fuzzy control; unknown measurement sensitivity; simplified backstepping approach
- Citation
- IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, v.69, no.6, pp.2862 - 2866
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
- Volume
- 69
- Number
- 6
- Start Page
- 2862
- End Page
- 2866
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/143007
- DOI
- 10.1109/TCSII.2022.3151417
- ISSN
- 1549-7747
- Abstract
- This brief investigates the adaptive tracking control problem for a class of nonlinear multi-agent systems with unknown measurement sensitivity using a simplified backstepping approach. By introducing Nussbaum gain, a new approach is proposed that effectively relaxes the restrictive condition that the unknown measurement sensitivity be within a particular range. A simplified backstepping approach is then presented to alleviate the structural complexity and high computational costs. It is proven that the tracking error converges to a small neighborhood of the origin and that all of the signals are bounded. Finally, simulation analysis is conducted to verify the effectiveness of the proposed control strategy.
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