Prescribed performance neural control to guarantee tracking quality for near space kinetic kill vehicle

doi:10.21629/JSEE.2019.03.15

Journal of Systems Engineering and Electronics ›› 2019, Vol. 30 ›› Issue (3): 573-586.doi: 10.21629/JSEE.2019.03.15

• Control Theory and Application • Previous Articles Next Articles

Prescribed performance neural control to guarantee tracking quality for near space kinetic kill vehicle

Tao ZHANG(), Jiong LI*(), Weimin LI(), Huaji WANG(), Humin LEI()

Air and Missile Defense College, Air Force Engineering University, Xi'an 710051, China

Received:2018-08-13 Online:2019-06-01 Published:2019-07-04
Contact: Jiong LI E-mail:zhangtaov2016@163.com;graceful001@126.com;liweimin@163.com;whj20081744@163.com;hmleinet@21cn.com
About author:ZHANG Tao was born in 1992. He received his bachelor's degree from Northwestern Polytechnical University in 2016 and master's degree from Air Force Engineering University in 2018. He is currently a Ph.D. candidate in Air and Missile Defense College, Air Force Engineering University. His research interests are the guidance control technology of the interceptor in near space with side window. E-mail:zhangtaov2016@163.com|LI Jiong was born in 1979. He received his B.S. degree in 2000, M.S. degree in 2003 and Ph.D. degree in 2007 from Air Force Engineering University, respectively. He is currently an associate professor and a supervisor for masters in Air and Missile Defense College, Air Force Engineering University. His research interests include the guidance, control and simulation of the hypersonic interceptor. E-mail:graceful001@126.com|LI Weimin was born in 1964. He received his B.S. degree in 1983, M.S. degree in 1986 from Air Force Engineering University, respectively, and his Ph.D. degree in 1989 from University of Electronic Science and Technology. He is currently a professor and a supervisor for doctors in Air and Missile Defense College, Air Force Engineering University. His current research interests lie in the field of air and space defense system and engineering. E-mail:liweimin@163.com|WANG Huaji was born in 1988. He received his B.S. degree in 2013 and M.S. degree in 2015 from Air Force Engineering University, respectively. He is a Ph.D. candidate in control theory and engineering at Air and Missile Defense College, Air Force Engineering University. His current research interests focus on the hypersonic interception, cooperative guidance law design, and capture region analysis. E-mail:whj20081744@163.com|LEI Humin was born in 1960. He received his M.S. and Ph.D. degrees from Northwestern Polytechnical University, in 1989 and 1999. He is now a professor and a supervisor for doctors in Air and Missile Defense College, Air Force Engineering University, Xi'an, China. His current research interests lie in the field of advanced guidance law design, hypersonic vehicle controller design and hypersonic interception strategy. E-mail:hmleinet@21cn.com
Supported by:
the National Natural Science Foundation of China(61773398);the National Natural Science Foundation of China(61703421);This work was supported by the National Natural Science Foundation of China (61773398; 61703421)

Abstract

Abstract:

A prescribed performance neural controller to guarantee tracking quality is addressed for the near space kinetic kill vehicle (NSKKV) to meet the state constraints caused by side window detection. Different from the traditional prescribed performance control in which the shape of the performance function is constant, this paper exploits new performance functions which can change the shape of their function according to different symbols of initial errors and can ensure the error convergence with a small overshoot. The neural backstepping control and the minimal learning parameters (MLP) technology are employed for exploring a prescribed performance controller (PPC) that provides robust tracking attitude reference trajectories. The highlight is that the transient performance of tracking errors is satisfactory and the computational load of neural approximation is low. The pseudo rate (PSR) modulator is used to shape the continuous control command to pulse or on-off signals to meet the requirements of the thruster. Numerical simulations show that the proposed method can achieve state constraints, pseudo-linear operation and high accuracy.

Key words: prescribed performance control, near space kinetic kill vehicle (NSKKV), neural approximation, minimal learning parameter (MLP), pseudo rate (PSR) modulator

Tao ZHANG, Jiong LI, Weimin LI, Huaji WANG, Humin LEI. Prescribed performance neural control to guarantee tracking quality for near space kinetic kill vehicle[J]. Journal of Systems Engineering and Electronics, 2019, 30(3): 573-586.

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References 33

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Parameter	Initial value
$\vartheta _0 $/($^\circ$)	10
$\psi _0 $/($^\circ$)	10
$\gamma _0 $/($^\circ$)	10
$\omega _{x0} /(^\circ /{{\rm{s}}})$	0.5
$\omega _{y0} /(^\circ /{{\rm{s}}})$	0.5
$\omega _{z0} /(^\circ /{{\rm{s}}})$	0.5

Parameter	Parameter perturbation
$d_x $	$3^\circ \sin \left(\dfrac{{\rm{ \mathsf{ π} }} }{2}t\right)$
$d_y $	$3^\circ \sin \left(\dfrac{{\rm{ \mathsf{ π} }} }{2}t\right)$
$d_z $	$3^\circ \sin \left(\dfrac{{\rm{ \mathsf{ π} }} }{2}t\right)$
$\Delta J_x $	$J_{x0} \times 20\% \sin (t)$
$\Delta J_y $	$J_{x0} \times 30\% \sin (t)$
$\Delta J_z $	$J_{z0} \times 10\% \sin (t)$
$\Delta l$	$l\times 20\% \sin (t)$
$\Delta r$	$r\times 20\% \sin (t)$

Channel	Pitch channel	Yaw channel	Roll channel
Switch times	223	220	291
Total consumption (N$\times$s)	47.790 0	19.048 5	40.392 0

Channel	Pitch channel	Yaw channel	Roll channel
Switch times	81	131	163
Total consumption (N$\times$s)	27.810 0	12.933 0	25.416 0

PWPF	PSR
$K_m = 4$	$K_m = 2$
$T_m = 0.5$	$T_m = 0.3$
$U_{{{\rm{on}}}} = 0.5$	$U_{{{\rm{on}}}} = 0.45$
$U_{{{\rm{on}}}} = 0.12$	$U_{{{\rm{on}}}} = 0.3$

Prescribed performance neural control to guarantee tracking quality for near space kinetic kill vehicle

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