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              面向戰機大迎角機動過程的智能學習控制

              于目航 王霞 楊林 許斌

              于目航, 王霞, 楊林, 許斌. 面向戰機大迎角機動過程的智能學習控制. 自動化學報, 2024, 50(4): 719?730 doi: 10.16383/j.aas.c230642
              引用本文: 于目航, 王霞, 楊林, 許斌. 面向戰機大迎角機動過程的智能學習控制. 自動化學報, 2024, 50(4): 719?730 doi: 10.16383/j.aas.c230642
              Yu Mu-Hang, Wang Xia, Yang Lin, Xu Bin. Intelligent learning control for fighter maneuvers at high angle of attack. Acta Automatica Sinica, 2024, 50(4): 719?730 doi: 10.16383/j.aas.c230642
              Citation: Yu Mu-Hang, Wang Xia, Yang Lin, Xu Bin. Intelligent learning control for fighter maneuvers at high angle of attack. Acta Automatica Sinica, 2024, 50(4): 719?730 doi: 10.16383/j.aas.c230642

              面向戰機大迎角機動過程的智能學習控制

              doi: 10.16383/j.aas.c230642
              基金項目: 國家自然科學基金 (61933010), 陜西省自然科學基礎研究計劃(2023JC-XJ-08)資助
              詳細信息
                作者簡介:

                于目航:西北工業大學博士研究生. 2022年獲得西北工業大學學士學位. 主要研究方向為飛行器智能控制. E-mail: yumh_npu@163.com

                王霞:山東大學博士后. 分別于2017年, 2020年和2023年獲得西北工業大學學士, 碩士和博士學位. 主要研究方向為智能控制, 自適應控制及其在飛行器中的應用. E-mail: wangxia_nwpu@163.com

                楊林:成都飛機設計研究所研究員. 主要研究方向為飛行控制系統設計. E-mail: 17311317089@163.com

                許斌:西北工業大學教授. 2006年獲得西北工業大學學士學位. 2012年獲得清華大學博士學位. 主要研究方向為智能控制, 自適應控制及其應用. 本文通信作者. E-mail: smileface.binxu@gmail.com

              Intelligent Learning Control for Fighter Maneuvers at High Angle of Attack

              Funds: Supported by National Natural Science Foundation of China (61933010) and Natural Science Basic Research Plan in Shaanxi (2023JC-XJ-08)
              More Information
                Author Bio:

                YU Mu-Hang Ph.D. candidate at Northwestern Polytechnical University. He received his bachelor degree from Northwestern Polytechnical University in 2022. His main research interest is intelligent control of flight dynamics

                WANG Xia Postdoctor at Shandong University. She received her bachelor, master and Ph.D. degrees from Northwestern Polytechnical University in 2017, 2020 and 2023, respectively. Her research interest covers intelligent control and adaptive control with applications to flight dynamics

                YANG Lin Researcher at Chengdu Aircraft Design & Research Institute. His main research interest is aircraft flight control system design

                XU Bin Professor at Northwestern Polytechnical University. He received his bachelor degree from Northwestern Polytechnical University in 2006, and received his Ph.D. degree from Tsinghua University in 2012. His research interest covers intelligent control and adaptive control with applications. Corresponding author of this paper

              • 摘要: 針對戰機大迎角動力學呈現的強非線性、氣動不確定和通道耦合特性, 提出了一種基于智能學習的自適應機動跟蹤控制方法. 通過將通道耦合視為集總擾動的一部分, 把模型分解為迎角子系統、側滑角子系統和滾轉角速率子系統. 采用神經網絡估計不確定, 設計跟蹤誤差反饋與集總干擾估計前饋相結合的控制器獲取期望操縱力矩, 并基于串接鏈分配方法求解氣動舵偏角和推力矢量偏角. 對于神經網絡權重更新, 構建預測誤差表征集總干擾的估計性能, 結合跟蹤誤差設計復合學習更新律. 基于李雅普諾夫方法證明了閉環系統的一致最終有界穩定性. 針對眼鏡蛇機動和赫伯斯特機動指令進行了仿真驗證和抗干擾參數拉偏測試, 結果表明所提方法具有較高的機動指令跟蹤精度和魯棒性能.
              • 圖  1  迎角子系統控制框圖

                Fig.  1  Angle of attack control diagram

                圖  2  眼鏡蛇機動迎角跟蹤((a) 指令跟蹤; (b) 跟蹤誤差)

                Fig.  2  Angle of attack tracking under Cobra maneuver ((a) Command tracking; (b) Tracking error)

                圖  3  眼鏡蛇機動$f_\alpha$的估計值((a) 基于NN-CL的$\hat f_\alpha$;(b) 基于NN的$\hat f_\alpha$; (c) 估計誤差)

                Fig.  3  Estimation of $f_\alpha$ under Cobra maneuver ((a) $\hat f_\alpha$ under NN-CL; (b) $\hat f_\alpha$ under NN; (c) Estimation error)

                圖  4  眼鏡蛇機動的操縱偏轉量((a) 升降舵; (b) 俯仰推矢偏角)

                Fig.  4  Control surface deflection under Cobra maneuver ((a) Elevator; (b) Pitch thrust vector deflection angle)

                圖  5  赫伯斯特機動迎角跟蹤((a) 指令跟蹤; (b) 跟蹤誤差)

                Fig.  5  Angle of attack tracking under Herbst maneuver ((a) Command tracking; (b) Tracking error)

                圖  6  赫伯斯特機動滾轉角速率跟蹤((a) 指令跟蹤; (b) 跟蹤誤差)

                Fig.  6  Roll angle rate tracking under Herbst maneuver ((a) Command tracking; (b) Tracking error)

                圖  7  赫伯斯特機動飛行狀態((a) 側滑角;(b) 速度; (c) 航跡方位角)

                Fig.  7  Flight states under Herbst maneuver ((a) Sideslip angle; (b) Speed; (c) Flight path azimuth angle)

                圖  8  赫伯斯特機動飛行軌跡

                Fig.  8  Flight path under Herbst maneuver

                圖  9  赫伯斯特機動氣動操縱舵面偏轉((a) 升降舵; (b) 副翼; (c) 方向舵)

                Fig.  9  Aerodynamic control surfaces deflection under Herbst maneuver ((a) Elevator; (b) Aileron; (c) Rudder)

                圖  10  赫伯斯特機動推力矢量偏轉((a)滾轉推矢偏角; (b)偏航推矢偏角; (c)俯仰推矢偏角)

                Fig.  10  Thrust vector nozzles deflection under Herbst maneuver ((a) Roll thrust vector deflection angle; (b) Yaw thrust vector deflection angle; (c) Pitch thrust vector deflection angle)

                圖  11  赫伯斯特機動$f_\alpha$的估計值((a) 基于NN-CL的$\hat f_\alpha$; (b) 基于NN的$\hat f_\alpha$; (c) 估計誤差)

                Fig.  11  Estimation of $f_\alpha$ under Herbst maneuver ((a) $\hat f_\alpha$ under NN-CL; (b) $\hat f_\alpha$ under NN; (c) Estimation error)

                圖  14  赫伯斯特機動$f_p$的估計值((a) 基于NN-CL的$\hat f_p$; (b) 基于NN的$\hat f_p$; (c) 估計誤差)

                Fig.  14  Estimation of $f_p$ under Herbst maneuver ((a) $\hat f_p$ under NN-CL; (b) $\hat f_p$ under NN; (c) Estimation error)

                圖  15  神經網絡權重估計值 ((a) $\|\hat{{\boldsymbol{\omega}}}_{f_\alpha}\|$; (b) $\|\hat{{\boldsymbol{\omega}}}_{f_q}\|$; (c) $\|\hat{{\boldsymbol{\omega}}}_{f_r}\|$; (d) $\|\hat{{\boldsymbol{\omega}}}_{f_p}\|$)

                Fig.  15  Estimation of NN weights ((a) $\|\hat{{\boldsymbol{\omega}}}_{f_\alpha}\|$; (b) $\|\hat{{\boldsymbol{\omega}}}_{f_q}\|$; (c) $\|\hat{{\boldsymbol{\omega}}}_{f_r}\|$; (d) $\|\hat{{\boldsymbol{\omega}}}_{f_p}\|$)

                圖  16  魯棒測試((a) 迎角; (b) 側滑角; (c) 滾轉角速率)

                Fig.  16  Robustness verification ((a) Angle of attack; (b) Sideslip angle; (c) Roll angle rate)

                圖  12  赫伯斯特機動$f_q$的估計值((a) 基于NN-CL的$\hat f_q$; (b) 基于NN的$\hat f_q$; (c) 估計誤差)

                Fig.  12  Estimation of $f_q$ under Herbst maneuver ((a) $\hat f_q$ under NN-CL; (b) $\hat f_q$ under NN; (c) Estimation error)

                圖  13  赫伯斯特機動$f_r$的估計值((a) 基于NN-CL的$\hat f_r$; (b) 基于NN的$\hat f_r$; (c) 估計誤差)

                Fig.  13  Estimation of $f_r$ under Herbst maneuver ((a) $\hat f_r$ under NN-CL; (b) $\hat f_r$ under NN; (c) Estimation error)

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