无人机集群分布式跟踪抗扰控制设计与实验验证

doi:10.13229/j.cnki.jdxbgxb.20221143

Abstract

Abstract:

The distributed trajectory tracking problem for multiple UAVs under unknown external disturbance is investigated. A new nonlinear robust trajectory tracking strategy for multiple UAVs is proposed. The dynamic model for the UAVs' formation is illustrated in the Tangent frame. For the trajectory tracking problem， a robust formation tracking control strategy based on robust integral of the signum of error （RISE） is designed to compensate for the effects of unknown external disturbances， which improves the robustness of the UAVs' formation system. Based on the Lyapunov stability analysis， it is proved that the global asymptotic convergence of the coordination errors and the semi-global asymptotic convergence of the UAVs' position tracking errors are achieved. The proposed formation control strategy is validated via real-time experiments that are performed on the self-build UAVs' formation flight control testbed. Flights without wind disturbance and flights with disturbance are all performed. The performance comparison experiment with the conventional sliding mode control algorithm is performed. The experimental results show that the designed control strategy can achieve good coordinated trajectory tracking of multiple UAVs， and has better control performance compared with normal sliding mode control law.

Key words: control science and engineering, UAV formation, distributed trajectory tracking control, cooperative control, disturbance rejection control, experimental verification

CLC Number:

TP273

Bin XIAN,Yin-xin WANG,Ling WANG. Distributed robust tracking control for multiple unmanned aerial vehicles： theory and experimental verification[J].Journal of Jilin University(Engineering and Technology Edition), 2024, 54(7): 2093-2103.

Figures/Tables 14

Fig.1

Fig.2

Fig.3

Table 1

Parameters of experiment"

参数名称	参数值
$r d$	$[0,0, 1] T$
$Λ$	$d i a g ([5,10,10] T)$
$D v$	$d i a g ([9,9, 9] T)$
$k s$	$d i a g ([3,2, 1.5] T)$
$λ$	$d i a g ([2,1.6,2] T)$
$α$	$d i a g ([0.08,0.12,0.05] T)$
$β$	$d i a g ([0.006,0.008,0.006] T)$

Table 1

Fig.4

Fig.5

Fig.6

Fig.7

Fig.8

Fig.9

Table 2

Error analysis of trajectory tracking position of multiple UAVs in experiment 1"

误差通道	SMC最大误差	RISEC最大误差	SMC均方根误差	RISEC均方根误差
$e 1 x / m$	0.161 1	0.024 0	0.060 2	0.008 7
$e 1 y / m$	0.287 6	0.024 2	0.114 4	0.008 3
$e 1 z / m$	0.045 7	0.021 7	0.016 2	0.008 2
$e 2 x / m$	0.270 6	0.061 4	0.096 6	0.024 7
$e 2 y / m$	0.239 4	0.039 5	0.082 1	0.015 5
$e 2 z / m$	0.058 2	0.030 6	0.017 0	0.014 4
$e 3 x / m$	0.246 4	0.073 0	0.108 8	0.021 5
$e 3 y / m$	0.212 9	0.083 4	0.088 1	0.024 7
$e 3 z / m$	0.044 3	0.042 9	0.015 4	0.014 8

Table 2

Fig.10

Table 3

Error analysis of trajectory tracking position of multiple UAVs in experiment 2"

误差通道	SMC 最大误差	RISEC 最大误差	SMC 均方根误差	RISEC 均方根误差
$e 1 x / m$	0.244 1	0.057 3	0.090 8	0.019 1
$e 1 y / m$	0.354 3	0.077 5	0.165 0	0.024 0
$e 1 z / m$	0.067 9	0.042 9	0.014 3	0.018 8
$e 2 x / m$	0.209 6	0.066 7	0.105 3	0.028 0
$e 2 y / m$	0.229 0	0.053 6	0.098 2	0.019 6
$e 2 z / m$	0.036 7	0.032 9	0.012 3	0.014 4
$e 3 x / m$	0.303 2	0.069 5	0.116 1	0.021 8
$e 3 y / m$	0.200 9	0.076 8	0.104 5	0.031 4
$e 3 z / m$	0.031 2	0.063 6	0.011 7	0.020 4

Table 3

Fig.11

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