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Second-order bipartite consensus for networked robotic systems with quantized-data interactions and time-varying
Teng-Fei Ding1, Ming-Feng Ge1, Cai-Hua Xiong2
1School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan 430074, China.
ISA Transactions
|August 31, 2020
Summary
This study addresses bipartite consensus (BC) in networked robotic systems (NRSs) with uncertainties. New hierarchical control algorithms (HCAs) achieve BC despite quantized data and time delays.
Area of Science:
- Robotics
- Control Theory
- Networked Systems
Background:
- Networked robotic systems (NRSs) face challenges like model uncertainties and external disturbances.
- Achieving bipartite consensus (BC) is crucial for coordinated behavior in NRSs.
- Existing methods often do not account for practical constraints like data quantization and time delays.
Purpose of the Study:
- To investigate second-order bipartite consensus (BC) problems for NRSs.
- To develop novel hierarchical control algorithms (HCAs) for BC under practical conditions.
- To analyze the stability and performance of NRSs with HCAs.
Main Methods:
- Development of two classes of hierarchical control algorithms (HCAs).
- Application of Hurwitz criterion for stability analysis.
- Utilization of Lyapunov stability arguments to derive control conditions.
- Analysis of bipartite consensus performance under quantized-data interactions (QDIs) and time-varying transmission delays (TVTDs).
Main Results:
- Sufficient conditions for achieving BC in NRSs with uncertainties and disturbances were derived.
- The proposed HCAs effectively address the challenges of QDIs and TVTDs.
- The BC performance of the regulated NRSs was analyzed and validated.
- Theoretical findings were confirmed through three illustrative examples.
Conclusions:
- The presented HCAs offer a robust solution for second-order BC problems in NRSs.
- The study provides a theoretical framework for designing controllers for NRSs with practical communication constraints.
- The findings contribute to the advancement of coordinated control in networked robotic systems.
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