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1. INTRODUCTION
With the rapid development of computer technology and networks, distributed cooperative control has drawn
increasingattentionduetoitsapplicationinvariousfields, especiallycomputerscienceandautomationcontrol.
A fundamental and important research topic of distributed system control is the consensus problem of multi-
agent systems. It has attracted considerable interest among many researchers in different fields in the past few
decades, due to its significant applications in civilians and militaries, such as unmanned air vehicles [1–3] , au-
[4]
[5]
tonomous underwater vehicles , multiple surface vessels , robot formation [6,7] . The consensus problem es-
sentially refers to a team of agents reaching the same state by designing proper and available distributed control
algorithms that only utilize local information exchange with neighbors. Over the past decade, there have been
a wealth of interesting and instructive achievements focusing on consensus problem of multi-agent systems,
including leaderless consensus [8–13] and leader-following consensus [14–21] . The leaderless output consensus
problemofmulti-agentsystemscomposed ofagentswith different orders was studied by transforming the orig-
inal system through feedback linearization. Static feedback and dynamic feedback controllers are designed to
solve the consensus problem and sinusoidal synchronization problem under uniformly jointly strongly con-
[8]
nected topologies . Under cyber-attacks, literature [9] proposed a fully distributed adaptive control protocol
to solve the leaderless consensus problem of uncertain high-order nonlinear systems. The work [11] discussed
theevent-triggeredcoordinationproblemforgenerallinearmulti-agentsystemsbasedonaLyapunovequation
method. Leader-following consensus means that the states of all follower agents are expected to approach the
state of the leader agent. In many practical situations, leader-following consensus can accomplish more com-
plex tasks by enhancing inter-agent communication. Compared with leaderless consensus, leader-following
consensus can be beneficial in reducing control costs and save energy. The key to the leader-follower consen-
sus problem is how to design a distributed control protocol to synchronize the states of all follower agents and
the leader agent. The work [14] proposed a novel distributed observer-type consensus controller for high-order
stochastic strict feedback multi-agent systems based only on relative output measurements of neighbors. The
1-moment exponential leader-following consensus of the underlying system is ensured by adopting appropri-
ate state transformation. In [15] , the sampled-data leader-following consensus problem for a family of general
linear multi-agent systems was addressed, and the distributed asynchronous sampled-data state feedback con-
trol law was designed. The event-based secure leader-following consensus control problem of multi-agent
systems with multiple cyber attacks, which contain reply attacks and DoS attacks simultaneously, was studied
in [16] . The fixed-time leader-following group consensus of multi-agent systems composed of first-order inte-
grators was realized under a directed graph [17] . By designing a nonlinear distributed controller, the follower
agents of every group can reach an agreement with its corresponding leader within a specified convergence
time. In [19] , the author considered the problem of resilient practical cooperative output regulation of heteroge-
neous linear multi-agent systems, in which the dynamics of exosystem are unknown and switched under DOS
attacks. A new cooperative output regulation scheme consisting of distributed controller, distributed resilient
observer, auxiliary observer and data-driven learning algorithm was proposed to ensure the global uniform
boundedness of the regulated output. More results can be seen in [18,20,21] and references cited therein.

It is well known that there is a large amount of data transmission in the control process of multi-agents. Data
packets or signals between agents are usually transmitted through wireless communication networks. How-
ever, some special physical phenomena (such as reflection, refraction, diffraction) may occur during the trans-
mission of a signal or data packet through a communication link or channel, which will result in the loss of
signal energy and lead to the signal distorted. This type of phenomenon is often referred to the channel fading.
Typically, fading effects are closely related to multipath propagation and shadows from obstacles. In practical
applications, the factors that cause channel fading mainly include time, geographic location, and radar fre-
quency. As a result, the phenomenon of channel fading may result in the degradation of signal quality due to
the inability to receive accurate transmission information, thereby deteriorating the desired performance of
the system. This also shows that it is meaningful to consider channel fading effects for the distributed control
of multi-agent systems. In view of this, some results on channel fading have been published, such as chan-