自适应飞机驾驶员最优控制模型研究及应用

doi:10.7527/S1000-6893.2015.0222

Abstract

Abstract:

The traditional optimal control pilot model (OCM) is based on Kalman filter which cannot reveal the pilot behavior in time varying disturbance of unknown environment. To overcome the omissions of OCM, a Modified optimal control pilot model based on adaptive state estimate (MOCM-AE) is developed, and the algorithm implementation is given. By magnitude and phase comparison in frequency domain, the MOCM-AE is testified through flight test reproduction. And the MOCM-AE is more identical to the measurements than OCM. In carrier landing application, the OCM depends on the priori experience grievously, and the MOCM-AE shakes off the fetters of the prior knowledge. In unknown low altitude disturbance, it improves the landing accuracy by 59% and reduces the touchdown point dispersion scope by 29%. The advantage are shown in the model evaluation and MOCM-AE is more proper to describe the pilot behavior in unknown environment.

Key words: carrier landing, pilot model, optimal control, unknown disturbance, state estimate

CLC Number:

V212.1

LIU Jia, XIANG Jinwu, ZHANG Ying, SUN Yang, XIAO Chuwan. Research and application of adaptive optimal control pilot model[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2016, 37(4): 1127-1138.

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Research and application of adaptive optimal control pilot model

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