Novel Adaptive Robust Roll Control Method Based on LESO

doi:10.12382/bgxb.2022.0106

Abstract

Abstract:

The roll channel mathematical model of missiles flying at large angles of attack is characterized by severe nonlinearity, instability, multivariable coupling, and uncertainty. An adaptive robust control method is designed to solve the issues. A linear extended state observer (LESO) is used to estimate aerodynamic nonlinear perturbations based on finite information of the missile. A novel adaptive sliding mode control law is employed together with a LESO to estimate and compensate disturbance online. The rapid adjustment of adaptive parameters can ensure the stability of the system and shorten the response time, thereby allowing for rapid convergence of the roll angle and roll angle rate, weakening chattering, and enhancing disturbance rejection ability. The simulation results show that the proposed control method has significant improvements in rapidity and robustness compared to traditional linear methods and also exhibits fault-tolerant control ability in typical fault handling scenarios.

Key words: roll channel control, sliding mode control, extended state observer, adaptive robust control

WANG Zhilin, WANG Jiang, QI Qi, FAN Shipeng. Novel Adaptive Robust Roll Control Method Based on LESO[J]. Acta Armamentarii, 2023, 44(7): 1920-1929.

Figures/Tables 10

Table 1 Parameter of the roll channel dynamic model

参数	取值
Cl_r	[0,200]
ω_RR/(rad·s^-1)	2
K_δ	[1000,3000]
ϕ
$ϕ ·$
传感器阻尼ξ_g	0.5
传感器带宽ω_g/(rad·s^-1)	200
δ_α	[-10°,10°]

Table 1 Parameter of the roll channel dynamic model

参数	取值
Cl_r	[0,200]
ω_RR/(rad·s^-1)	2
K_δ	[1000,3000]
ϕ
$ϕ ·$
传感器阻尼ξ_g	0.5
传感器带宽ω_g/(rad·s^-1)	200
δ_α	[-10°,10°]

Fig.1 Schematic diagram of the controller

Table 2 Control parameter setting

参数	k_a	k_b	η	μ	Φ	ω₀
数值	8	130	2	0.8	0.3	15

Fig.2 Parameter changes of the roll channel

Fig.3 Simulation of roll channel control system under different flight conditions

Fig.4 Adaptive parameter variation

Fig.5 Control effect comparison at f=0.3

Fig.6 Simulation results at f=0.3

Fig.7 Simulation results at f=0.5

Fig.8 Simulation results at f=0.9

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