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Consensus of Multi-Agent Systems with Input Constraints Based on Distributed Predictive Control Scheme

Yueqi Hou1, Xiaolong Liang1, 2, Lyulong He1, Jiaqiang Zhang1, *, Jie Zhu3, Baoxiang Ren3

1 National Key Laboratory of Air Traffic Collision Prevention, Air Force Engineering University, Xi’an, 710051, China.
2 Shanxi Province Laboratory of Meta-Synthesis for Electronic and Information System, Xi’an, 710051, China.
3 Air Traffic Control and Navigation College, Air Force Engineering University, Xi’an, 710051, China.

* Corresponding Author: Jiaqiang Zhang. Email:

Computers, Materials & Continua 2020, 62(3), 1335-1349.


Consensus control of multi-agent systems has attracted compelling attentions from various scientific communities for its promising applications. This paper presents a discrete-time consensus protocol for a class of multi-agent systems with switching topologies and input constraints based on distributed predictive control scheme. The consensus protocol is not only distributed but also depends on the errors of states between agent and its neighbors. We focus mainly on dealing with the input constraints and a distributed model predictive control scheme is developed to achieve stable consensus under the condition that both velocity and acceleration constraints are included simultaneously. The acceleration constraint is regarded as the changing rate of velocity based on some reasonable assumptions so as to simplify the analysis. Theoretical analysis shows that the constrained system steered by the proposed protocol achieves consensus asymptotically if the switching interaction graphs always have a spanning tree. Numerical examples are also provided to illustrate the validity of the algorithm.


Cite This Article

Y. Hou, X. Liang, L. He, J. Zhang, J. Zhu et al., "Consensus of multi-agent systems with input constraints based on distributed predictive control scheme," Computers, Materials & Continua, vol. 62, no.3, pp. 1335–1349, 2020.


This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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