The Bridge - Issue 2, 2018 - 23

Distributed Stochastic Optimal Flocking Control for Uncertain Networked Multi-Agent Systems

IV. SIMULATION RESULTS
In this section, a practical networked nonlinear
MAS example is used to evaluate the proposed
stochastic optimal flocking control design. Consider
the following nonlinear multiple unmanned aircraft
system (multi-UAS) as:

in Figure 3, each sub-group is able to ensure its
optimal flocking performance. Moreover, using the
communication between the sub-groups, the ten
networked UAS can also achieve the overall optimal
flocking simultaneously.

(17)
where the dynamics of the multi-UAS,
, are defined as in [2]. Furthermore,
assuming that all the UAS are operating at the same
height [3], then, the position of each UAS can be
represented in a two-dimensional space. The initial
positions of the UAS are generated randomly in a
100m*100m region by using the norm distribution
function. Moreover, velocities for multi-UAS are
initialized as zeroes.
(a)

Figure 3. The trajectories of ten UAS

To evaluate the generality of proposed scheme,
the flocking performance of the proposed MAS
algorithm considering ten agents has been studied.
Based on the communication graph, the ten UAS
have been separated as two sub-groups, and only
a cluster head UAS in each sub-group was allowed
to communication between sub-groups. As shown

(b)
Figure 4. (a) Networked MAS testbed; (b) Experimental
application where networked UAS perform an
autonomous mission to track a moving ground vehicle.

Furthermore, the effectiveness of the proposed
finite horizon stochastic optimal flocking design has
been evaluated through a networked multi-UAS

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Table of Contents for the Digital Edition of The Bridge - Issue 2, 2018

Contents
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