基于QSS的自适应多步校正算法及其在柔性航天器动力学中的应用

doi:10.7527/S1000-6893.2020.24455

固体力学与飞行器总体设计

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基于QSS的自适应多步校正算法及其在柔性航天器动力学中的应用

李志华, 李广, 沈汉武, 樊志华

杭州电子科技大学机械工程学院, 杭州 310018

收稿日期:2020-06-24 修回日期:2020-08-18 出版日期:2021-06-15 发布日期:1900-01-01
通讯作者: 李志华 E-mail:D98LZH@263.net
基金资助:
浙江省自然科学基金（LY18E050008，LY19E050013）；国家重点研发计划（2017YFB1301300）

QSS based adaptive multi-step correction algorithm and its application in flexible spacecraft dynamics

LI Zhihua, LI Guang, SHEN Hanwu, FAN Zhihua

School of Mechanical Engineering, Hangzhou Dianzi University, Hangzhou 310018, China

Received:2020-06-24 Revised:2020-08-18 Online:2021-06-15 Published:1900-01-01
Supported by:
Natural Science Foundation of Zhejiang Province(LY18E050008,LY19E050013); National Key R&D Program of China (2017YFB1301300)

摘要/Abstract

摘要： 量化状态系统（QSS）算法是一种基于状态变量离散化的数值积分方法，该方法与基于时间离散的传统方法显著不同，QSS通过计算状态变量每次跃迁所需的时间来推进下一步的积分。在求解非刚性常微分方程时，QSS算法比传统算法更具优势，但它不适合求解刚性问题。为此提出一种基于QSS的自适应多步校正算法（AMCQSS），该算法以QSS为基础、结合隐式多步法思想，在计算过程中可以自适应选择二步法或三步法，以有效提高求解刚性问题的精度和效率。通过对柔性航天器动力学的仿真求解，验证了算法的可行性。将该算法与ODE23tb、ODE15s、ODE45以及QSS等算法进行对比，结果表明AMCQSS算法既能保证求解的效率及精度，又具有较好的收敛性和稳定性。

关键词: 量化状态系统, 数值积分, 刚性问题, 柔性航天器, 动力学

Abstract: Quantized State System (QSS) is a new numerical integration method based on discretization of state variables. Different from traditional time discretization methods, QSS advances the next integration by calculating the time required for each transition of the state variables. Despite its advantages over traditional methods in solving non-stiff ordinary differential equations, it is not suitable for solving stiff problems. Therefore, an adaptive multi-step correction algorithm based on QSS (AMCQSS) is proposed, combining the ideas of the QSS method and the implicit multi-step method. The AMCQSS can adaptively choose two-step or three-step methods in the calculation process to effectively improve the accuracy and efficiency of solving stiff problems. The feasibility of this algorithm is verified by the simulation of flexible spacecraft dynamics. The comparison of performance between this algorithm and the previous methods of ODE23tb, ODE15s, ODE45 and QSS shows that the AMCQSS can ensure the solution efficiency and accuracy with good convergence and stability.

Key words: quantized state system, numerical integration, stiff problem, flexible spacecraft, dynamics

中图分类号:

李志华, 李广, 沈汉武, 樊志华. 基于QSS的自适应多步校正算法及其在柔性航天器动力学中的应用[J]. 航空学报, 2021, 42(6): 224455-224455.

LI Zhihua, LI Guang, SHEN Hanwu, FAN Zhihua. QSS based adaptive multi-step correction algorithm and its application in flexible spacecraft dynamics[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(6): 224455-224455.

参考文献

[1] 徐世杰. 柔性航天器动力学建模与在轨振动控制研究[D]. 哈尔滨:哈尔滨工业大学,2019:1-9. XU S J. Research on flexible spacecraft dynamics modeling and on-orbit vibration control[D]. Harbin:Harbin Institute of Technology, 2019:1-9(in Chinese).
[2] 曹登庆,白坤朝,丁虎,等. 大型柔性航天器动力学与振动控制研究进展[J]. 力学学报,2019,51(1):1-13. CAO D Q, BAI K C, DING H, et al. Advances in research on dynamics and vibration control of large flexible spacecraft[J]. Journal of Mechanics, 2019, 51(1):1-13(in Chinese).
[3] 黄文虎,曹登庆,韩增尧. 航天器动力学与控制的研究进展与展望[J]. 力学进展,2012, 42(4):367-394. HUANG W H, CAO D Q, HAN Z Y. Research progress and prospect of spacecraft dynamics and control[J]. Advances in Mechanics, 2012, 42(4):367-394(in Chinese).
[4] WASFY T, NOOR A. Computational strategy of flexible multi-body system[J]. Advances in Mechanics, 2006, 56(6):553-613.
[5] SCHIEHLEN W. Computational dynamics:Theory and applications of multibody systems[J]. European Journal of Mechanics, 2006, 25(4):566-594.
[6] BROGLIATO B, TEN A, PAOLI L, et al. Numerical simulation of finite dimensional multibody non-smooth mechanical systems[J]. Applied Mechanics Reviews, 2002, 55(2):107-149.
[7] GEAR C W. Numerical initial value problems in ordinary differential equations[M]. Upper Saddle River:Prentice Hall, Inc, 1971:1-17.
[8] BUTCHER J C. Implicit Runge-Kutta processes[J]. Mathematics of Computation, 1964, 18(85):50-64.
[9] ZEIGLER B P, LEE J S. Theory of quantized systems:Formal basis for DEVS/HLA distributed simulation environment[J]. Proceedings of SPIE the International Society for Optical Engineering, 1998, 3369(1):49-58.
[10] KOFMAN E, JUNCO S. Quantized-state systems:A DEVS approach for continuous system simulation[J]. Transactions of the Society for Modeling and Simulation International, 2001, 18(1):2-8.
[11] KOFMAN E. Discrete event simulation of hybrid systems[M]. New York:Springer, 2004:1-21.
[12] KOFMAN E. A Second-order approximation for DEVS simulation of continuous systems[J]. Simulation, 2002, 78(2):76-89.
[13] KOFMAN E. A third order discrete event method for continuous system simulation[J]. Latin American Applied Research, 2006,36(2):101-108.
[14] BERGERO F, CASELLA F, KOFMAN E, et al. On the efficiency of quantization-based integration methods for building simulation[J]. Building Simulation, 2017, 11(2):1-14.
[15] MIGONI G, KOFMAN E. Linearly implicit discrete event methods for stiff ODE's[J]. Latin American Applied Research, 2009, 39(3):245-254.
[16] MIGONI G, KOFMAN E, CELLIER F. Quantization-based new integration methods for stiff ordinary differential equations[J]. Simulation, 2012, 88(4):118-136.
[17] MIGONI G, BORTOLOTTO M, KOFMAN E, et al. Linearly implicit quantization-based integration methods for stiff ordinary differential equations[J]. Simulation Modelling Practice and Theory, 2013, 35(6):118-136.
[18] 朱雨童,王江云,韩亮. 基于量化状态积分的空间目标温度计算[J]. 红外与激光工程,2011, 40(12):2345-2348. ZHU Y T, WANG J Y, HAN L. Space target temperature calculation based on quantized state integration[J]. Infrared and Laser Engineering, 2011, 40(12):2345-2348(in Chinese).
[19] 檀添,赵争鸣,李帛洋,等. 基于离散状态事件驱动的电力电子瞬态过程仿真方法[J]. 电工技术学报, 2017, 32(13):41-50. TAN T, ZHAO Z M, LI B Y, et al. A transient process simulation method for power electronics based on discrete state event-driven[J]. Transactions of China Electrotechnical Society, 2017, 32(13):41-50(in Chinese).
[20] 李帛洋,赵争鸣,檀添,等. 后向离散状态事件驱动电力电子仿真方法[J]. 电工技术学报,2017, 32(12):42-49. LI B Y, ZHAO Z M, TAN T, et al. A backword discrete state event driven simulation method for power electronics based on finite state machine[J]. Transactions of China Electrotechnical Society, 2017, 32(12):42-49(in Chinese).
[21] 王维. 基于Modelica的量化状态系统方法实现及其特性分析[D]. 武汉:华中科技大学,2017:14-25. WANG W. Quantized state system method implementation and its characteristic analysis based on Modelica[D]. Wuhan:Huazhong University of Science and Technology, 2017:14-25(in Chinese).
[22] 李志华,吴晨佳,江德,等. 基于量化状态系统的柔性关节机器人动力学求解方法[J]. 机械工程学报, 2020, 56(3):121-129. LI Z H, WU C J, JIANG D, et al. The dynamics solving method of flexible joint robot based on quantized state system[J]. Journal of Mechanical Engineering, 2020, 56(3):121-129(in Chinese).
[23] 余舜京,丰志伟,张青斌. 柔性航天器动力学建模及模型降阶研究[J]. 计算机仿真,2011, 28(6):80-83, 108. YU S J, FENG Z W, ZHANG Q B. Research on dynamics modeling and model reduction of flexible spacecraft[J]. Computer Simulation, 2011, 28(6):80-83, 108(in Chinese).
[24] 王钦. 航天器姿态和挠性附件动力学分析与仿真验证研究[D]. 长沙:国防科技大学,2011:16-33. WANG Q. Dynamics analysis and simulation verification of spacecraft attitude and flexible appendages[D]. Changsha:National University of Defense Science and Technology, 2011:16-33(in Chinese).
[25] 罗文. 太阳翼卫星的刚柔耦合动力学建模[D]. 哈尔滨:哈尔滨工业大学,2015:22-36. LUO W. Rigid flexible coupling dynamics modeling of solar wing satellite[D]. Harbin:Harbin Institute of Technology, 2015:22-36(in Chinese).
[26] 陶然. 挠性自旋卫星角动量转移过程分析与仿真[D]. 哈尔滨:哈尔滨工业大学,2017:21-30. TAO R. Analysis and Simulation of angular momentum transfer process of flexible spin satellite[D]. Harbin:Harbin Institute of Technology, 2017:21-30(in Chinese).
[27] 刘敏,徐世杰,韩潮. 挠性航天器的退步直接自适应姿态跟踪控制[J]. 航空学报,2012, 33(9):1697-1705. LIU M, XU S J, HAN C. Direct adaptive attitude tracking control for flexible spacecraft based on backstepping method[J]. Acta Aeronautica et Astronautica Sinica, 2012, 33(9):1697-1705(in Chinese).
[28] PIETRO F D, MIGONI G, KOFMAN E. Improving a linearly implicit quantized state system method[C]//Winter Simulation Conference.Piscataway:IEEE Press, 2016:1084-1095.

E-mail：hkxb@buaa.edu.cn

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基于QSS的自适应多步校正算法及其在柔性航天器动力学中的应用

QSS based adaptive multi-step correction algorithm and its application in flexible spacecraft dynamics

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