Control allocation for a class of morphing aircraft with integer constraints based on Lévy flight

doi:10.23919/JSEE.2020.000056

Journal of Systems Engineering and Electronics ›› 2020, Vol. 31 ›› Issue (4): 826-840.doi: 10.23919/JSEE.2020.000056

• Control Theory and Application • Previous Articles Next Articles

Control allocation for a class of morphing aircraft with integer constraints based on Lévy flight

Yao LU^1,^2,*(), You SUN^1,²(), Xiaodong LIU^1,²(), Bo GAO^1,²()

¹ Beijing Aerospace Automatic Control Institute, Beijing 100854, China
² National Key Laboratory of Science and Technology on Aerospace Intelligence Control, Beijing 100854, China

Received:2019-05-05 Online:2020-08-25 Published:2020-08-25
Contact: Yao LU E-mail:luyaosacred@126.com;sunyou1979@126.com;k.start@163.com;buaa@126.com
About author:LU Yao was born in 1987. He received his Ph.D. degree in flight vehicle design from Beihang University in 2017. He is currently an engineer in Beijing Aerospace Automatic Control Institute. His research interests include nonlinear control and intelligence control. E-mail: luyaosacred@126.com|SUN You was born in 1979. He received his M.S. degree in guidance, navigation and control from Beijing Institute of Technology in 2004. He is currently a professor of engineering in Beijing Aerospace Automatic Control Institute. His research interests include missile guidance and control, guided projectile, and fault detection. E-mail: sunyou1979@126.com|LIU Xiaodong was born in 1987. He received his Ph.D. degree in guidance, navigation and control from Beihang University in 2013. He is currently an engineer in Beijing Aerospace Automatic Control Institute. His research interests include hypersonic flight control, integrated guidance and control and intelligence control. E-mail: k.start@163.com|GAO Bo was born in 1986. He received his M.S. degree in guidance, navigation and control from Beihang University in 2011. He is currently an engineer in Beijing Aerospace Automatic Control Institute. His research interests include robotic control and fuzzy control. E-mail: gaobo1986 buaa@126.com
Supported by:
the National Natural Science Foundation of China(61803357);This work was supported by the National Natural Science Foundation of China (61803357)

Abstract

Abstract:

Aiming at tracking control of a class of innovative control effector (ICE) aircraft with distributed arrays of actuators, this paper proposes a control allocation scheme based on the Lévy flight. Different from the conventional aircraft control allocation problem, the particular characteristic of actuators makes the actuator control command totally subject to integer constraints. In order to tackle this problem, first, the control allocation problem is described as an integer programming problem with two desired objectives. Then considering the requirement of real-time, a metaheuristic algorithm based on the Lévy flight is introduced to tackling this problem. In order to improve the searching efficiency, several targeted and heuristic strategies including variable step length and inherited population initialization according to feedback and so on are designed. Moreover, to prevent the incertitude of the metaheuristic algorithm and ensure the flight stability, a guaranteed control strategy is designed. Finally, a time-varying simulation model is introduced to verifying the effectiveness of the proposed scheme. The contrastive simulation results indicate that the proposed scheme achieves superior tracking performance with appropriate actuator dynamics and computational time, and the improvements for efficiency are active and the parameter settings are reasonable.

Key words: flight control, control allocation, optimization, Lévy flight, tracking control

Yao LU, You SUN, Xiaodong LIU, Bo GAO. Control allocation for a class of morphing aircraft with integer constraints based on Lévy flight[J]. Journal of Systems Engineering and Electronics, 2020, 31(4): 826-840.

Figures/Tables 17

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References 26

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Statistics	$\lambda = 1.8$	$\lambda = 2$	$\lambda = 2.3$	$\lambda = 2.5$	$\lambda = 2.8$
Number of random walks	10 000	10 000	10 000	10 000	10 000
Number of $\|l(\lambda)\| \le 1$/ Average of all $\|l(\lambda)\| \le 1$	5 363/0.407 4	5 013/0.446 7	3 532/0.485 5	2 128/0.494 4	426/0.502 9
Number of $1 < \|l(\lambda)\| \le 2.5$/Average of all $1 < \|l(\lambda)\| \le 2.5$	2 171/1.591 8	2 550/1.589 8	3 053/ 1.640 5	2 660/1.701 2	605/1.746 9
Number of $2.5 < \|l(\lambda)\| \le 5$/ Average of all $2.5 < \|l(\lambda)\|\le 5$	1 048/3.527 7	1 113/3.467 3	1 791/3.489 2	2 502/3.590 8	942/3.708 4
Number of $5 < \|l(\lambda)\| \le 10$/Average of all $5 < \|l(\lambda)\| \le 10$	591/7.062 2	630/ 6.983 3	935/6.799 3	1 664/6.938 4	1 737/7.417 2
Number of $\|l(\lambda)\| > 10$/ Average of all $\|l(\lambda)\| > 10$	827/28.358	694/26.475	689/22.777	1 046/ 22.230	6 290/26.758
Average of all $\|l(\lambda)\|$	3.696 4	3.292 5	3.502 3	4.935 9	18.596

Boundary	$n_1$	$n_2$	$n_3$	$n_4$	$n_5$	$n_6$	$n_7$	$n_8$
$\underline{n}_i$	-12	-5	-12	-5	-12	-12	-10	-10
$\overline {n}_i$	12	5	12	5	12	12	10	10

Experiment number	Initial condition
1	${\mathit{\boldsymbol{v}}}(t) = [-2.000~0, 6.500~0]^{\rm{T}}, {\mathit{\boldsymbol{v}}}(t-1) = [0, 0]^{\rm{T}}, $ ${{\boldsymbol{n}}}_p = [0, 0, 0, 0, 0, 0, 0, 0]^{\rm{T}}, \vartheta = 0.5$
2	${\mathit{\boldsymbol{v}}}(t) = [-2.500~0, 7.000~0]^{\rm{T}}, {\mathit{\boldsymbol{v}}}(t-1)= $ $[-2.500~0, 7.000~0]^{\rm{T}}, $ ${{\boldsymbol{n}}}_p = [-7, -3, 2, 1, 5, -5, - 1, - 1]^{\rm{T}}, \vartheta = 0.5$

Scheme	Experiment 1		Experiment 2
Scheme	Mean	Standard	Mean	Standard
Contrastive scheme	13.047 3	7.918 7	13.028 0	7.973 2
The proposed scheme	10.345 7	4.010 3	3.640 5	3.957 0

Scheme	Experiment 1		Experiment 2
Scheme	Mean	Standard	Mean	Standard
Contrastive scheme	0.289 0	0.130 6	0.134 4	0.035 3
The proposed scheme	0.120 3	0.046 6	0.066 7	0.037 8

Control allocation for a class of morphing aircraft with integer constraints based on Lévy flight

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Scheme	$\lambda _g = 2.5, \lambda _l = 2.0$		$\lambda _g = 2.8, \lambda _l = 2.0$		$\lambda _g = 2.5, \lambda _l = 2.3$		$\lambda _g = 2.3, \lambda _l = 2.0$		$\lambda _g = 2.5, \lambda _l = 1.8$
Scheme	Mean	Standard	Mean	Standard	Mean	Standard	Mean	Standard	Mean	Standard
The proposed scheme	0.118 8	0.051 9	0.179 7	0.099 3	0.196 3	0.145 5	0.127 9	0.058 8	0.167 5	0.078 2

Scheme	Accumulated $\Delta V$ per flight process/ (m/s)	Accumulated $\Delta p$ per flight process/ ((°)/s)	Accumulated $\Delta r$ per flight process/ ((°)/s)	Accumulated $\Delta \phi $ per flight process/ (°)
Contrastive scheme	11.470 3	109.914 5	10.815 5	45.668 4
The proposed scheme	4.2914	28.506 9	2.775 6	22.899 4

Scheme	Number of state switches per sample point
Scheme	$n_1 $	$n_2 $	$n_3 $	$n_4 $	$n_5 $	$n_6 $	$n_7 $	$n_8 $
Contrastive scheme	7.663	3.844	7.595	4.003	7.809	7.045	6.986	5.763
The proposed scheme	1.210	0.757	1.223	0.770	1.416	1.264	1.043	0.846

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