Work

Adaptive Fuzzy Leader-Following Consensus Quantized Control for High-Order Nonlinear Multi-Agent Systems

Year: 2025

Type: article

Abstract: This paper investigates the adaptive fuzzy leader-following consensus control problem for a class of high-order nonlinear multi-agent systems with quantized input signals. Considering the complex dynamics of high-order nonlinear multi-agent systems, a novel adaptive fuzzy control strategy with equivalent virtual controller is proposed to achieve the consensus tracking performance and guarantee the uniform ultimate boundedness of the closed-loop nonlinear system. During the control design process, only the states information from the subsystem itself and its neighbors and part of the information from the reference signals are available. In addition, the hysteresis quantizer is utilized to reduce the chattering phenomenon. Finally, a numerical simulation example is given to show the effectiveness of the proposed control strategy.

Source: Actuators

DOI: 10.3390/act14110552

Authors: Yifan Liu, Min Ma, Tong Wang

Institutions: Soochow University, Harbin Institute of Technology

Language: English

Topic: Distributed Control Multi-Agent Systems

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,896

Funders: National Natural Science Foundation of China, Government of Jiangsu Province, Natural Science Foundation of Jiangsu Province