Tight upper bound for the scrambling constant of uniformly jointly-connected graphs with application to consensus of multi-agent systems

Author(s):  
Chao Huang ◽  
Gang Feng ◽  
Hao Zhang ◽  
Huaicheng Yan
2020 ◽  
Vol 5 (2) ◽  
pp. 112-125
Author(s):  
Kazuki Miyakoshi ◽  
Shun Ito ◽  
Hidetoshi Oya ◽  
Yoshikatsu Hoshi ◽  
Shunya Nagai

This paper proposed a linear matrix inequality (LMI)-based design method of non-fragile guaranteed cost controllers for multi-agent systems (MASs) with leader-follower structures. In the guaranteed cost control approach, the resultant controller guarantees an upper bound on the given cost function together with asymptotical stability for the closed-loop system. The proposed non-fragile guaranteed cost control system can achieve consensus for MASs despite control gain perturbations. The goal is to develop an LMI-based sufficient condition for the existence of the proposed non-fragile guaranteed cost controller.  Moreover, a design problem of an optimal non-fragile guaranteed cost controller showe that minimizing an upper bound on the given quadratic cost function can be reduced to constrain a convex optimization problem. Finally, numerical examples were given to illustrate the effectiveness of the proposed non-fragile controller for MASs.


2017 ◽  
Vol 40 (8) ◽  
pp. 2651-2659 ◽  
Author(s):  
Mali Xing ◽  
Feiqi Deng

This paper aims to solve the scaled consensus problem of general linear multi-agent systems with non-uniform time-varying communication time-delay. The proposed consensus protocol is based on the low gain solution of a parametric algebraic Riccati equation. Based on the proposed consensus protocol, we obtain the sufficient condition for scaled consensus of multi-agent systems with communication time-delay. The results reveal that the upper bound of time-delay can be arbitrarily large if all poles of the system are zero. For the case of non-zero poles on the imaginary axis, the maximal admissible upper bound of the time-varying delay is provided. Simulation results are performed to demonstrate the scaled consensus performance of multi-agent systems.


Sign in / Sign up

Export Citation Format

Share Document