Journal of Systems Engineering and Electronics ›› 2021, Vol. 32 ›› Issue (4): 947-955.doi: 10.23919/JSEE.2021.000081

• CONTROL THEORY AND APPLICATION • Previous Articles     Next Articles

Research on consensus of multi-agent systems with and without input saturation constraints

Duo QI1,2(), Junhua HU3,*(), Xiaolong LIANG1,2(), Jiaqiang ZHANG1,2(), Zhihao ZHANG1,2()   

  1. 1 Air Traffic Control and Navigation College, Air Force Engineering University, Xi’an 710051, China
    2 Shaanxi Province Lab. of Meta-Synthesis for Electronic & Information System, Xi’an 710051, China
    3 Aeronautical Engineering College, Air Force Engineering University, Xi’an 710038, China
  • Received:2020-07-06 Online:2021-08-18 Published:2021-09-30
  • Contact: Junhua HU E-mail:qi33song@sina.com;56811366@ qq.com;afeu_lxl@sina.com;jiaqiang-z@163.com;408691252@qq.com
  • About author:|QI Duo was born in 1987. He received his M.S. degree of weapon system and application engineering, and Ph.D. degree of armament science and technology from the Aeronautical Engineering College, Air Force Engineering University in 2012 and 2016 respectively. He is a lecturer at the Air Traffic Control and Navigation College, Air Force Engineering University. His research interests are aviation swarm technology and airspace management intelligence. E-mail: qi33song@sina.com||HU Junhua was born in 1980. He received his Ph.D. degree of armament science and technology from the Aeronautical Engineering College, Air Force Engineering University in 2008. Now he is an assistant professor in the Aeronautical Engineering College, Air Force Engineering University. His research interest is multi-agent system. E-mail: 56811366@ qq.com||LIANG Xiaolong was born in 1981. He received his M.S. degree of operational research and cybernetics, and Ph.D. degree of armament science and technology from the Air Force Engineering University. He is a professor in Air Traffic Control and Navigation College, Air Force Engineering University. His research interests are aircraft swarm technology, airspace management intelligence, and intelligent aviation system. E-mail: afeu_lxl@sina.com||ZHANG Jiaqiang was born in 1984. He received his M.S. degree of weapon system and application engineering, and Ph.D. degree of armament science and technology in the Aeronautical Engineering College, Air Force Engineering University in 2009 and 2012 respectively. He is a lecturer in the Air Traffic Control and Navigation College, Air Force Engineering University. His research interests are aviation cluster technology and airspace management intelligence. E-mail: jiaqiang-z@163.com||ZHANG Zhihao was born in 1989. He received his M.S. degree of navigation engineering from Air Force Engineering University in 2014. He is a lecturer in the Air Traffic Control and Navigation College, Air Force Engineering University. His research interests are aviation swarm technology and airspace management intelligence. E-mail: 408691252@qq.com
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (61703427)

Abstract:

In recent years, with the continuous development of multi-agent technology represented by unmanned aerial vehicle (UAV) swarm, consensus control has become a hot spot in academic research. In this paper, we put forward a discrete-time consensus protocol and obtain the necessary and sufficient conditions for the second-order consensus of the second-order multi-agent system with a fixed structure under the condition of no saturation input. The theoretical derivation verifies that the two eigenvalues of the Laplacian of the communication network matrix and the sampling period have an important effect on achieving consensus. Then we construct and verify sufficient conditions to achieve consensus under the condition of input saturation constraints. The results show that consensus can be achieved if velocity, position gain, and sampling period satisfy a set of inequalities related to the eigenvalues of the Laplacian matrix. Finally, the accuracy and validity of the theoretical results are proved by numerical simulations.

Key words: multi-agent system, consensus control, input constraint, distributed control