[1] 方洋旺, 柴栋, 毛东辉, 等. 吸气式高超声速飞行器制导与控制研究现状及发展趋势[J]. 航空学报, 2014, 35(7): 1776-1786. FANG Y W, CHAI D, MAO D H, et al. Status and development trend of the guidance and control for air-breathing hypersonic vehicle[J]. Acta Aeronautica et Astronautica Sinica, 2014, 35(7): 1776-1786.(in Chinese) [2] 赵江, 周锐, 张超. 考虑禁飞区规避的预测校正再入制导方法[J]. 北京航空航天大学学报, 2015, 41(5): 864-870. ZHAO J, ZHOU R, ZHANG C. Predictor-corrector reentry guidance satisfying no-fly zone constraints[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(5): 864- 870. (in Chinese) [3] SCHULTZ R L, ANDERSON P, STOLARIK E. A simple gui-dance scheme for lifting body reentry vehicles[C]∥Proceedings of the 5th Aerospace Sciences Meeting. New York, NY, US: AIAA, 1967:136. [4] LU P. Predictor-corrector entry guidance for low-lifting vehicles[J]. Journal of Guidance, Control, and Dynamics, 2008, 31(4): 1067-1075. [5] XUE S, LU P. Constrained predictor-corrector entry guidance[J]. Journal of Guidance, Control, and Dynamics, 2010, 33(4): 1273-1281. [6] 冉茂鹏, 王青, 莫华东,等. 基于自适应神经模糊系统的高超声速飞行器再入预测制导[J]. 兵工学报, 2014, 35(12): 2016-2022. RAN M P, WANG Q, MO H D, et al.ANFIS-based predictive reentry guidance for hypersonic vehicles[J]. Acta Armamentarii, 2014, 35(12): 2016-2022. (in Chinese) [7] 程阳, 程林, 张庆振, 等. 基于在线约束限制的飞行器预测校正制导[J]. 北京航空航天大学学报, 2017, 43(10): 2143-2153. CHENG Y, CHENG L, ZHANG Q Z, et al. Aircraft predictor-corrector guidance based on online constraint limit enforcement[J]. Journal of Beijing University of Aeronautics and Astronautics, 2017, 43(10): 2143-2153. (in Chinese) [8] 王肖, 唐胜景, 祁帅, 等. 带终端高度约束的再入预测校正制导[J]. 战术导弹技术, 2018(4): 70-77. WANG X, TANG S J, QI S, et al. Predictor-corrector entry gui-dance with terminal altitude constraint[J]. Tactical Missile Technology, 2018(4): 70-77. (in Chinese) [9] 张鹏, 都延丽, 项凯. 高升阻比RLV的约束预测校正再入制导[J]. 飞行力学, 2018, 36(3): 70-74. ZHANG P, DU Y L, XIANG K. Constrained predictive-corrector reentry guidance for high lift-to-drag RLV[J]. Flight Dynamics, 2018, 36(3): 70-74. (in Chinese)
[10] SCHIERMAN J D, WARD D G, HULL J R, et al. Integrated adaptive guidance and control for re-entry vehicles with flight-test results[J]. Journal of Guidance, Control, and Dynamics, 2004, 27(6): 975-988. [11] 解永锋, 唐硕. 基于伪谱法的亚轨道返回轨迹在线重构方法[J]. 飞行力学, 2011, 29(6): 63-67. XIE Y F, TANG S. On-line trajectory reshaping of suborbital return entry via pseudospectral method[J]. Flight Dynamics, 2011, 29(6): 63-67. (in Chinese) [12] 钱佳淞, 齐瑞云. 基于NFTET的高超声速飞行器再入容错制导[J]. 航空学报, 2015, 36 (10): 3370-3381. QIAN J S, QI R Y. Fault-tolerant guidance for reentry hypersonic flight vehicles based on NFTET[J]. Acta Aeronautica et Astronautica Sinica, 2015,36 (10): 3370-3381. (in Chinese) [13] 焦李成, 杨淑媛, 刘芳,等. 神经网络七十年:回顾与展望[J]. 计算机学报, 2016, 39(8): 1697-1716. JIAO L C, YANG S Y, LIU F, et al. Seventy years beyond neural networks: retrospect and prospect[J]. Chinese Journal of Computers, 2016, 39(8): 1697-1716.(in Chinese) [14] 孙志军, 薛磊, 许阳明, 等. 深度学习研究综述[J]. 计算机应用研究, 2012, 29(8): 2806-2810. SUN Z J, XUE L, XU Y M, et al. Overview of deep learning[J]. Application Research of Computers, 2012, 29(8): 2806-2810. (in Chinese) [15] 王青,莫华东,吴振东, 等. 基于能量的高超声速飞行器再入混合制导方法[J]. 北京航空航天大学学报, 2014, 40(5): 580-585. WANG Q, MO H D, WU Z D, et al. Energy-based hybrid guidance for hypersonic vehicles[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(5): 580-585. (in Chinese) [16] ZHAO J, ZHOU R, JIN X L. Gauss pseudospectral method applied to multi-objective spacecraft trajectory optimization[J]. Journal of Computational and Theoretical Nanoscience, 2014, 11(10): 2242-2246. [17] 潘乐飞, 李新国. 可重复使用运载器预测-校正再入制导研究[J]. 飞行力学, 2007, 25(1): 55-58. PAN L F, LI X G. Study of predictor-corrector reentry guidance for reusable launch vehicles[J]. Flight Dynamics, 2007, 25(1): 55-58. (in Chinese) [18] HINTON G E, OSINDERO S, TEH Y W. A fast learning algorithm for deep belief nets[J]. Neural Computation, 2006, 18(7): 1527-1554. [19] HINTON G E, DENG L, YU D, et al. Deep neural networks for acoustic modeling in speech recognition: the shared views of four research groups[J]. IEEE Signal Processing Magazine, 2012, 29(6): 82-97. [20] 任谢楠. 基于遗传算法的BP神经网络的优化研究及MATLAB仿真[D]. 天津:天津师范大学, 2014. REN X N. Study on optimization of BP neural network based on genetic algorithm and MATLAB simulation[D]. Tianjin:Tianjin Normal University, 2014. (in Chinese)
[21] HAN J Q. From PID to active disturbance rejection control[J]. IEEE Transactions on Industrial Electronics, 2009, 56(3): 900-906. [22] YU Y, WANG H L, LI N, et al. Automatic carrier landing system based on active disturbance rejection control with a novel parameters optimizer[J]. Aerospace Science and Technology, 2017, 69: 149-160.
第41卷第4期2020 年4月 兵工学报ACTA ARMAMENTARII Vol.41No.4Apr.2020
|