Cooperative Control of Multi-UAV with Time Constraint
in The Threat Environment
MA Pei-bei, FAN Zuo-e,JI Jun
Abstract—Cooperative control strategy can support
coordinated attack for multi-UAV in threat environment, and
achieve the greatest combat effectiveness with time constraint.
It is a crucial problem with significant theoretical value and
great practical value. Firstly, a cooperative path planning based
expanded Voronoi diagram was proposed. The threat
environments considered different types of threats and no-fly
zones with different threat distances. Line-of-sight of path
shortening algorithm and smoothing algorithm were proposed
to realize dynamic optimization of the paths. Secondly, time
error signal was obtained from real time-to-go and the
estimated time-to-go by adopting a simple online time-to-go
estimation method. Dynamic path planning on the basis of the
estimated path was done to satisfy the impact time constraint.
At last, simulation results proved validity and real-time. This
method can support cooperative attack for multi-UAV.
I. INTRODUCTION
Modern information wars emphasize system resistance
and cooperative attack. The possibility of single-UAV attack
becomes less, while coordinated attack for multi-UAV is a
more modern ideas of information warfare methods of
warfare
[1,2]
. But effective collaborative control strategies for
supporting multiple UAVs under threat environment and meet
time constraints with the greatest probability of success, and
the lowest risk of hitting the target, at minimal cost, minimal
casualties for maximum operational efficiency, is a theoretical
and practical issues of significance, as well as hotspots of
aircraft control technology.
Study on multi-UAV cooperative control in the threat
environment is designed to maximize the use of terrain,
weather, threats, no-flight, and intelligence environmental
information, the use of UAV data link between recognition,
communication, navigation and the tactical information
sharing system for interaction on the flight path, effectively
organize together multiple UAVs’ target at completing
common tasks. Design path planning of UAV from the point
of departure to the destination point which can meet various
tactical performance of flight path together, and achieve
higher efficiency. Take full advantage of the resources, which
achieve better than a single UAV tactical effect
[3,4]
. But we
must recognize the multiple UAVs simultaneously from
different locations and directions on implementing
coordinated attack multiple targets, reaching the target time is
not exactly the same, and sometimes considerably, and may
cause enemy UAV combat ability to partially or fully recover
within a short time, thereby greatly influence our UAV
defense penetration probability and overall operational
effectiveness. Therefore, study the threat environment with
timing constraints under cooperative control of multiple
UAVs is extremely important.[5] proposed a cooperative path
planning method with the time constraints for a coordinated
variable and coordinated function together. [6] designed
impact time and impact angle control guidance law based on
virtual-leader.
min
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* Supported by the National Natural Science Foundation(61305136) and the
Aeronautical Science Foundation of China(20131384004)
Ma peibei Department of Command, Naval Aeronautic and Astronautical
University, Yantai, Shandong, 264001, e-mail:hympbok@yeah.net
Fan zuo-e Department of strategic missile and underwater weapon, Navy
Submarine academy, Qingdao, Shandong, 266044
Ji Jun Department of Command, Naval Aeronautic and Astronautical
University, Yantai, Shandong, 264001, e-mail:hyjjok@sina.com
.
Multi-UAV cooperative path planning algorithm was
presented. The threat environment considered no-fly zones
and the threat zones with different threat distances, threat
degrees and tactical values of the targets. In order to satisfy
maneuverable performance of the missiles, line of sight for
path shortening algorithm and smoothing algorithm were
proposed to realize dynamic optimization of the paths. The
algorithm could realize trajectory re-planning in dynamic
threat environment, and make multi-UAV attack different
targets from different terminal impact angles without collision
each other. The simulation results proved the algorithm was
effective and real-time.
II. M
ODELING WITH THE THREAT ENVIRONMENT
Usually, UAV can be intimidated by exploring and
destruction threats. Threat degree is inversely as the square of
the distance from UAV to threat source, such as the formula
(1)
KR R R R
RR
(1)
R is the distance between UAV and threat sourceˈ
222
()()()
ij ij ij
xx yy hh
(, ,)
iii
ˈ
yh
,)
jjj
is the
location of the threat sourceˈ
(,
yh
K
min
d
R
max
d
R
is the location of
the UAVˈ is tactical and technical index which is a
coefficient of reflection areaˈ and are the nearest
and farthest detection distances.
Threat of destruction mainly refers to various anti-air
missile, artillery, and so on. The threat probability
distributions subject to Gaussian distribution, thus
min
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(2)
2424
978-1-4799-4699-0/14/
31.00©2014 IEEE
Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference August 8-10, 2014 Yantai, China