基于自校正MPC的舰载机着舰控制技术

doi:10.12305/j.issn.1001-506X.2022.01.31

Abstract

Abstract:

In this paper, the carrier landing problem under the condition of model uncertainty is studied, and a self-tuning model predictive control method (ST-MPC) based on symplectic pseudospectral method (SP) and recursive least squares with forgetting factor (FFRLS) is established. Aiming at the carrier landing control model and in the framework of MPC method, a guidance trajectory based on the predicted shape and position deviation is designed to eliminate the influence of deck motion and real-time trajectory error. Meanwhile, the rock tail air wake compensation is introduced into the rolling optimization module based on SP algorithm to compensate the carrier air wake disturbance. Then, FFRLS with Butterworth low-pass filter is used to estimate the sensitive parameters in order to improve the robustness of the control algorithm. Simulation results show that the ST-MPC algorithm designed in this paper can control the height error within ±0.15 m with the disturbances are existed and the model parameters are not accurate, and its control accuracy is much higher than the traditional linear quadratic regulator and pole assignment algorithm. The calculation efficiency is also sufficient for real-time online tracking.

Key words: self-tuning, symplectic pseudospectral method, predictive control, carrier landing, parameter uncertainty

CLC Number:

V249.12

Wei HAN, Kaikai CUI, Jie LIU, Xinwei WANG, Yong ZHANG. Carrier landing control technology based on self-tuning MPC[J]. Systems Engineering and Electronics, 2022, 44(1): 250-261.

Figures/Tables 16

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状态/控制变量	取值约束
Δδ_H/(°)	[-12.14, 22.36]
Δδ_LEF/(°)	[-20.6, 15.4]
Δδ_RT/(°)	[-30, 30]
Δδ_T/rad	[-0.254, 0.756]
$\Delta {\dot \delta _H}$/(°/s)	[-40, 40]
$\Delta {\dot \delta _{{\rm{LEF}}}}$/(°/s)	[-15, 15]
$\Delta {\dot \delta _{{\rm{RT}}}}$/(°/s)	[-56, 56]
$\Delta {\dot \delta _{{\rm{T}}}}$/(rad/s)	[-0.55, 0.55]

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Carrier landing control technology based on self-tuning MPC

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