考虑性能约束的高超声速变体飞行器自适应优化控制

doi:10.7527/S1000-6893.2025.32387

Abstract

Abstract:

To address the strong nonlinearity， large uncertainties and multi-source external disturbances during the morphing process， an adaptive optimal control method with performance constraints for hypersonic morphing vehicles is proposed. Firstly， the steady-state controller is designed based on adaptive performance-prescribed control. The singularity problem of fixed performance function is solved by designing an adaptive scaling strategy. Furthermore， the optimal compensation controller is designed based on adaptive dynamic programming. Online optimal control is realized through offline-online policy iteration scheme， where offline policy iteration enhances the stability of the network in the initial stage of online updates， and online policy iteration enhances the robustness of the optimal compensation controller by introducing the zero-sum game. Finally， the stability of the closed-loop system is analyzed based on Lyapunov stability theorems. Simulation results show that the proposed method improves the transient and steady-state performance of the vehicle system. The results also illustrate that the proposed method improves the robustness and adaptability to uncertainties and external disturbances during morphing flight process.

Key words: hypersonic morphing vehicles, attitude control, performance-prescribed control, adaptive dynamic programming, policy iteration, zero-sum game

CLC Number:

V249.1

Jianxin SU, Yuxin LIAO, Weiping XU, Junyue TAN, Xing GAO. Adaptive optimal control for hypersonic morphing vehicles considering performance constraints[J]. Acta Aeronautica et Astronautica Sinica, 2026, 47(4): 332387.

Figures/Tables 14

Fig.1

Fig.2

Fig.3

Table 1

Parameters of control method

控制方法模块	参数	数值
稳态控制器	$τ$	0.002
	$η$	0.95
	P₀	5
	P_f	0.1
	K₁	［10，10，10］
	K₂	diag（15，15，15）
最优补偿控制器（离线策略迭代）	Q₁	diag（1，1，1）
最优补偿控制器（离线策略迭代）	P	diag（0.5，0.5，0.5）
最优补偿控制器（在线策略迭代）	$γ$	0.8
	$η c$	0.5
	$η a$	0.5
	$η d$	0.5
	Q	diag（1，1，1）
	R₁	diag（0.5，0.5，0.5）
	R₂	diag（0.5，0.5，0.5）
微分器	H	50
	$λ 1$	2
	$λ 2$	2
干扰观测器	$Γ 1$	diag（3，3，3）
	$Γ 2$	diag（5，5，5）
	$Γ 3$	diag（3，3，3）
	$Γ 4$	diag（5，5，5）

Table 1

Fig.4

Fig.5

Fig.6

Table 2

Model parameter uncertainty

工况	模型不确定性
工况	$Δ C m x / %$	$Δ C m y / %$	$Δ C m z / %$	$Δ ρ / %$
1	+30	+30	+30	+30
2			+30	-30
3			-30	+30
4			-30	-30
5		-30	+30	+30
6			+30	-30
7			-30	+30
8			-30	-30
9	-30	+30	+30	+30
10			+30	-30
11			-30	+30
12			-30	-30
13		-30	+30	+30
14			+30	-30
15			-30	+30
16			-30	-30

Table 2

Table 3

Attitude tracking control performance

性能指标	本文方法（均值）	对比方法（均值）
俯仰通道IAE/ $(°) ⋅ s - 1$	2.126 6	2.234 4
偏航通道IAE/ $(°) ⋅ s - 1$	1.853	2.255 2
滚转通道IAE/ $(°) ⋅ s - 1$	0.741 48	2.160 7
俯仰通道ITAE/ $(°) ⋅ s - 2$	4.786 9	4.622 8
偏航通道ITAE/ $(°) ⋅ s - 2$	3.429 6	5.625
滚转通道ITAE/ $(°) ⋅ s - 2$	7.249 9	13.010 9

Table 3

Fig.7

Fig.8

Fig.9

Fig.10

Fig.11

References 24

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Adaptive optimal control for hypersonic morphing vehicles considering performance constraints

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