Ultra-fast consensus of discrete-time multi-agent systems with multi-step predictive output feedback

Abstract

This article addresses the ultra-fast consensus problem of high-order discrete-time multi-agent systems based on a unified consensus framework. A novel multi-step predictive output mechanism is proposed under a directed communication topology containing a spanning tree. By predicting the outputs of a network several steps ahead and adding this information into the consensus protocol, it is shown that the asymptotic convergence factor is improved by a power of q + 1 compared to the routine consensus. The difficult problem of selecting the optimal control gain is solved well by introducing a variable called convergence step. In addition, the ultra-fast formation achievement is studied on the basis of this new consensus protocol. Finally, the ultra-fast consensus with respect to a reference model and robust consensus is discussed. Some simulations are performed to illustrate the effectiveness of the theoretical results.

Keywords:

• multi-agent systems
• output feedback
• ultra-fast consensus
• reference model
• external disturbances

Acknowledgements

The authors would like to thank the associate editor and four reviewers for their valuable comments and suggestions that have significantly improved the quality of this paper.

Additional information

Funding

This research work was supported by the National Natural Science Foundation [grant number 61374137]; IAPI Fundamental Research Funds [grant number 2013ZCX02-03]; the Fundamental Research Funds for the Central Universities [grant number N120604007].

Notes on contributors

Wenle Zhang

Wenle Zhang was born in Gaizhou City, Liaoning Province, P.R. China, in 1986. He received the BS degree in automation from Shenyang Jianzhu University, Shenyang, China, in 2009. He is currently pursuing the PhD degree after earning the MS degree in control theory and control engineering at Northeastern University, Shenyang, China, in 2011. His current research interests include consensus of multi-agent system, distributed optimisation, internal model principle, and nonlinear control systems.

Jianchang Liu

Jianchang Liu is a professor at the School of Information Science and Engineering, Northeastern University, Shenyang, China. His research interest covers modelling, control and optimisation for complex process, fault diagnosis, and intelligent control theory and application.