电光与控制, 2019, 26 (12): 22, 网络出版: 2021-01-30  

无人直升机着舰甲板运动预估与补偿方法

An Estimation and Compensation Method of Deck Motion for Unmanned Helicopter Landing on Ship
作者单位
1 海军工程大学兵器工程学院, 武汉 430033
2 中国人民解放军92925部队, 山西 长治 046000
摘要
无人直升机担负着越来越重要的作战使命, 而甲板运动是影响其着舰安全的重要因素, 对着舰甲板运动进行精确预估与补偿是亟待解决的难题。为此, 基于自适应AR模型与最优预见控制方法, 提出了一种甲板运动预估与补偿方法。基于AR模型设计甲板运动预估器时, 引入时变因子设计了自适应模型参数更新律优化模型性能, 强调数据的实时性, 仿真结果表明, 该方法在一定程度上提高了甲板运动预估的准确性, 且计算相对简单; 将甲板运动预估器产生的预估信号作为可预见的未来信息引入预见控制器, 并基于最优控制理论对着舰甲板运动进行补偿, 较好地改善了甲板运动补偿系统相位延迟问题, 并在一定程度上提高了甲板运动跟踪精度, 进而提高无人直升机着舰成功率。
Abstract
Unmanned helicopter is undertaking more and more important combat missions, and deck motion is an important factor affecting the safety of its autonomous landing, thus the accurate estimation and compensation of deck motion becomes an urgent problem. To solve the problem, a method of deck motion estimation and compensation based on adaptive AR model and optimal preview control is proposed. When designing the deck motion estimator based on AR model, the time-variant factor is introduced to design the updating law of the adaptive model parameters, so as to optimize model performance. Simulation results show that the proposed method improves the accuracy of deck motion estimation to a certain extent, and its computation process is relatively simple. Then, the prediction signals generated by the deck motion estimator are introduced into the preview controller as the foreseeable future information, and the deck motion of the landing point is compensated based on the optimal control theory. This method solves the problem of phase delay of deck motion compensation system effectively and improves the deck motion tracking accuracy to a certain extent, so that it can increase the success rate of unmanned helicopter autonomous landing.
参考文献

[1] 许东松, 刘星宇, 王立新. 航母运动对舰载飞机着舰安全性的影响[J]. 北京航空航天大学学报, 2011, 37(3): 289-294.

[2] 周鑫, 彭荣鲲, 袁锁中, 等. 舰载机着舰纵向甲板运动预估及补偿技术[J]. 南京航空航天大学学报, 2013, 45(5): 599-604.

[3] YANG X L. Displacement motion prediction of a landing deck for recovery operations of rotary UAVs[J]. International Journal of Control, Automation and Systems, 2013, 11(1): 58-64.

[4] 戴文正. 无人直升机自主着舰引导与控制技术研究[D]. 南京: 南京航空航天大学, 2014.

[5] 马坤, 甄子洋, 覃海群. 基于预见控制的甲板运动跟踪控制研究[J]. 电光与控制, 2017, 24(11): 74-77.

[6] KOO S, KIM S, SUK J. Model predictive control for UAV automatic landing on moving carrier deck with heave motion[J]. International Federation of Automatic Control- PapersOnLine, 2015, 48(5): 59-64.

[7] 侯敏, 甄子洋, 龚华军. 基于自适应AR模型的甲板运动预估技术[J]. 飞行力学, 2018, 36(3): 33-36.

[8] 黄誉. 无人直升机自主着舰关键技术研究[D]. 西安: 西北工业大学, 2015.

[9] YIN J C, PERAKIS A N, WANG N. A real-time ship roll motion prediction using wavelet transform and variable RBF network[J]. Ocean Engineering, 2018, 160: 10-19.

[10] LU K K, CHENG N, LI Q. Research and simulation on the carrier deck motion adaptive prediction for ACLS design[C]//IEEE Chinese Guidance, Navigation and Control Conference, 2014: 1341-1345.

[11] 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.

[12] ZHEN Z Y, JIANG S Y, MA K. Automatic carrier landing control for unmanned aerial vehicles based on preview control and particle filtering[J]. Aerospace Science and Technology, 2018, 81: 99-107.

[13] 甄子洋, 王志胜, 王道波. 基于信息融合估计的离散线性系统预见控制[J]. 自动化学报, 2010, 36(2): 347-352.

[14] YOUN I, KHAN M A, UDDIN N, et al. Road disturbance estimation for the optimal preview control of an active suspension systems based on tracked vehicle model[J]. International Journal of Automotive Technology, 2017, 18(2): 307-316.

[15] YOUN I, TCHAMNA R, LEE S H, et al. Preview suspension control for a full tracked vehicle[J]. International Journal of Automotive Technology, 2014, 15(3): 399-410.

吴鹏飞, 石章松, 吴中红, 郝翎钧. 无人直升机着舰甲板运动预估与补偿方法[J]. 电光与控制, 2019, 26(12): 22. WU Pengfei, SHI Zhangsong, WU Zhonghong, HAO Lingjun. An Estimation and Compensation Method of Deck Motion for Unmanned Helicopter Landing on Ship[J]. Electronics Optics & Control, 2019, 26(12): 22.

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!