基于船舶水动力的六自由度a&ω运动参数发生器

doi:10.12305/j.issn.1001-506X.2023.06.26

Abstract

Abstract:

Aiming at the problem that the trajectory and motion parameters generated by the traditional trajectory generator do not conform to the characteristics of the real ship, the hydrodynamic force and moment of the hull, propeller and rudder under different motion states are analyzed based on the separate structural model six-degree-of-freedom ship motion equation, and the six-degree-of-freedom linear acceleration and angular velocity (a&ω) model in static water condition is deduced. A second-order model of longitudinal linear acceleration is established based on the fixed speed of the gear, and the damping ratio and natural frequency of the second-order system are used to represent the acceleration and deceleration performance of the ship when the gear is switched. By adopting the recursive algorithm of maximum likelihood estimation, the unknown parameters in the model could be identified. Based on the measured data of a certain ship, the validity of the motion parameter generator is verified, and the simulation similarity is evaluated. The simulation results show that the generator can generate a total of 15-dimensional motion parameters such as linear acceleration, angular velocity, attitude, velocity and position, and the similarity of each motion parameter is more than 95%.

Key words: ship hydrodynamics, motion parameter generator, linear acceleration, angular velocity

CLC Number:

U666.11

Hongwei BIAN, Xian DING, Heng MA, Rongying WANG. A six-degree-of-freedom a&ω motion parameter generator based on ship hydrodynamics[J]. Systems Engineering and Electronics, 2023, 45(6): 1821-1827.

Figures/Tables 8

Fig.1

Fig.2

Table 1

Table 2

Table 3

Fig.3

Table 4

Fig.4

References 30

1	KARETNIKOV V, OL'KHOVIK E, BUTSANETS A, et al. Simulation of maneuvering trials of an unmanned or autonomous surface ship on a navigation simulator[C]//Proc. of the XⅢ International Scientific Conference on Architecture and Construction, 2021: 146-156.
2	ZHU Z L, WANG R Y, BIAN H W, et al. Research on integrated navigation information fusion simulation platform[C]//Proc. of the IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering, 2021: 350-354.
3	CHAE M S , CHO S Y , SHIN K H . Development of a real trajectory-based simulator to verify the reliability of the integrated navigation system for trains[J]. The Journal of the Korea Institute of Electronic Communication Sciences, 2021, 16 (1): 135- 144.
4	刘科, 吴文启, 唐康华, 等. 利用实际飞行数据插值的INS/GNSS组合导航仿真轨迹发生器[J]. 国防科技大学学报, 2018, 40 (1): 132- 137.
	LIU K , WU W Q , TANG K H , et al. Trajectory generator for INS/GNSS integration simulation through real flight data interpolation[J]. Journal of National University of Defense Techno-logy, 2018, 40 (1): 132- 137.
5	WOO J W , AN J Y , CHO M G , et al. Integration of path planning, trajectory generation and trajectory tracking control for aircraft mission autonomy[J]. Aerospace Science and Technology, 2021, 118, 107014. doi: 10.1016/j.ast.2021.107014
6	LETIZIA N A , SALAMAT B , TONELLO A M . A novel recursive smooth trajectory generation method for unmanned vehicles[J]. IEEE Trans.on Robotics, 2021, 37 (5): 1792- 1805. doi: 10.1109/TRO.2021.3053649
7	FUKUDA G , HATTA D , KUBO N . A study on estimation of acceleration and angular velocity data from actual measurements by trajectory generator[J]. The Journal of Japan Institute of Navigation, 2021, 144 (14): 14- 20.
8	VALERA , VALERO F , VALLES M , et al. Navigation of autonomous light vehicles using an optimal trajectory planning algorithm[J]. Sustainability, 2021, 13 (3): 1233. doi: 10.3390/su13031233
9	WANG S J , HE Z W . A prediction model of vessel trajectory based on generative adversarial network[J]. The Journal of Navigation, 2021, 74 (5): 1161- 1171. doi: 10.1017/S0373463321000382
10	QUAN W , FANG J C , XU F , et al. Hybrid simulation system study of SINS/CNS integrated navigation[J]. IEEE Aerospace and Electronic Systems Magazine, 2008, 23 (2): 17- 24. doi: 10.1109/MAES.2008.4460727
11	GOLOVAN A, ZHELEZNOV V, SMOLIANOV D, et al. Inflight inertial navigation system alignment under non-controlled delays in aiding data[C]//Proc. of the Journal of Physics: Conference Series, 2021: 012011.
12	张梦得, 胡柏青, 陈琪, 等. 船用指北平台式惯导模拟器中轨迹发生器设计[J]. 舰船科学技术, 2021, 43 (5): 146- 150.
	ZHANG M D , HU B Q , CHEN Q , et al. Design of trajectory generator in marine digital north platform inertial navigation simulator[J]. Ship Science and Technology, 2021, 43 (5): 146- 150.
13	罗宇锋, 刘勇. 基于轨迹发生器的捷联惯导算法仿真研究[J]. 河南理工大学学报(自然科学版), 2015, 34 (6): 867- 871.
	LUO Y F , LIU Y . Design and simulation of the trajectory gene-rator based on the strapdown inertial navigation vehicle[J]. Journal of Henan Polytechnic University (Natural Science), 2015, 34 (6): 867- 871.
14	张斌. 基于捷联惯导的舰船轨迹仿真发生器设计[J]. 数字技术与应用, 2009, 11 (3): 11- 13.
	ZHANG B . Design of ship trajectory simulation generator based on strapdown inertial navigation[J]. Digital Technology and Applications, 2009, 11 (3): 11- 13.
15	陈凯, 卫凤, 张前程, 等. 基于飞行力学的惯导轨迹发生器及其在半实物仿真中的应用[J]. 中国惯性技术学报, 2014, 22 (4): 486- 491.
	CHEN K , WEI F , ZHANG Q C , et al. Trajectory generator of SINS on flight dynamics with application in hardware-in-the-loop simulation[J]. Journal of Chinese Inertial Technology, 2014, 22 (4): 486- 491.
16	张秀凤, 尹勇, 金一丞. 规则波中船舶运动六自由度数学模型[J]. 交通运输工程学报, 2007, 7 (3): 40- 43.
	ZHANG X F , YIN Y , JIN Y C . Ship motion mathematical model with six degrees of freedom in regular wave[J]. Journal of Traffic and Transportation Engineering, 2007, 7 (3): 40- 43.
17	SUZUKI R , UENO M , TSUKADA Y . Numerical simulation of 6-degrees-of-freedom motions for a manoeuvring ship in regular waves[J]. Applied Ocean Research, 2021, 113, 102732.
18	TASAI F . Damping force and added mass of ships heaving and pitching (continued)[J]. Reports of Research Institute for Applied Machanics, 1960, 39 (8): 39- 74.
19	JI M M , XIANG Y . Modeling and simulation of ship motion for loading and unloading containers on the shore[J]. International Core Journal of Engineering, 2020, 6 (6): 69- 75.
20	SKJETNE R , SMOGELI N , FOSSEN T I . A nonlinear ship manoeuvering model: identification and adaptive control with experiments for a model ship[J]. Modeling, Identification & Control, 2004, 25 (1): 3- 27.
21	孙健, 陈永冰, 周岗, 等. 两种响应型船舶运动模型的对比及适用性分析[J]. 舰船科学技术, 2016, 38 (11): 14- 19.
	SUN J , CHEN Y B , ZHOU G , et al. The comparison and applicability analysis of two kinds of responding ship model[J]. Ship Science and Technology, 2016, 38 (11): 14- 19.
22	NOMOTO K , TAGUCHI T , HONDA K , et al. On the steering qualities of ships[J]. International Shipbuilding Progress, 1957, 4 (35): 354- 370.
23	李伟, 王洪民, 唐峥. 基于递推最小二乘法的转向系统参数辨识[J]. 重庆交通大学学报(自然科学版), 2019, 38 (8): 124- 128.
	LI W , WANG H M , TANG Z . Parameter identification of steering system based on recursive least square method[J]. Journal of Chongqing Jiaotong University(Natural Science), 2019, 38 (8): 124- 128.
24	ZHOU T , HASHEMINASAB S M , HABIB A . Tightly-coupled camera/LiDAR integration for point cloud generation from GNSS/INS-assisted UAV mapping systems[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2021, 180, 336- 356.
25	SAVAGE P G . Strapdown inertial navigation integration algorithm design part 1: attitude algorithms[J]. Journal of Gui-dance, Control, and Dynamics, 1998, 21 (1): 19- 28.
26	SAVAGE P G . Strapdown inertial navigation integration algorithm design part 2: velocity and position algorithms[J]. Journal of Gui-dance, Control, and Dynamics, 1998, 21 (2): 208- 221.
27	GISSIBL N , KLUPPELBERG C , LAURITZEN S . Identifiability and estimation of recursive max-linear models[J]. Scandinavian Journal of Statistics, 2021, 48 (1): 188- 211.
28	XIE S , CHU X M , LIU C G , et al. Parameter identification of ship motion model based on multi-innovation methods[J]. Journal of Marine Science and Technology, 2020, 25 (1): 162- 184.
29	WANG D Q , FAN Q H , MA Y . An interactive maximum likelihood estimation method for multivariable Hammerstein systems[J]. Journal of the Franklin Institute, 2020, 357 (17): 12986- 13005.
30	SONG R , CHEN X Y , FANG Y C , et al. Integrated navigation of GPS/INS based on fusion of recursive maximum likelihood IMM and square-root cubature Kalman filter[J]. ISA Transactions, 2020, 105, 387- 395.

档位	稳定航速/kn	ξ₁	ω₁
前进一	9	1.000 1	0.028 5
前进二	14	1.002 1	0.053 8
前进三	18	1.400 0	0.050 0
前进四	25	1.461 3	0.046 8

参数	数值	参数	数值
船长/m	135.0	船宽/m	16.0
船高/m	35.0	吃水/m	4.5
最高航速/kn	30.0	排水量/t	3 600.0

运动时间/s	运动状态	ΔV/kn
103	直线匀速	0
87	直线加速	4.6
326	直线匀速	0
75	回转减速	-4.1
19	回转匀速	0
15	回转加速	0.5
115	直线加速	3.3

参数	阈值	准确度/%
位置	66.50 m	97.43
航速	0.15 m/s	99.05
纵摇	0.50°	95.95
横摇	1.00°	96.22
航向	2.00°	95.95

[1]	LIN Hong-bin， XIE Jing， WANG Yan. Calibration method for IMU dynamic error based on sinusoidal linear acceleration [J]. Systems Engineering and Electronics, 2013, 35(10): 2152-2157.
[2]	DU Lin-lin, PAN Xu-dong, CHEN Zeng-peng. Analysis of rotation angles in ship target imaging based on missile-borne radar [J]. Journal of Systems Engineering and Electronics, 2011, 33(2): 301-304.
[3]	LIU Tao1, ZHAO Guo-rong2, PAN Shuang1. New calculating method of angular velocity in gyroscope-free strapdown inertial navigation systems [J]. Journal of Systems Engineering and Electronics, 2010, 32(1): 162-165.
[4]	HAO Yan-ling，LIU Zhi-ping. Application of weighted average method on angular velocity calculation of GFSINS [J]. Journal of Systems Engineering and Electronics, 2009, 31(12): 2934-2937.

A six-degree-of-freedom a&ω motion parameter generator based on ship hydrodynamics

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 8

References 30

Related Articles 4

Recommended Articles

Metrics

Comments