面向复杂系统运动仿真的信息物理融合建模

doi:10.16182/j.issn1004731x.joss.22-0097

系统仿真学报 ›› 2022, Vol. 34 ›› Issue (5): 954-963.doi: 10.16182/j.issn1004731x.joss.22-0097

• 专栏：面向复杂产品的建模仿真与优化 • 上一篇下一篇

面向复杂系统运动仿真的信息物理融合建模

刘文正(), 张和明()

清华大学　工业智能与系统研究所，北京　100090

收稿日期:2022-02-09 修回日期:2022-04-14 出版日期:2022-05-18 发布日期:2022-05-25
通讯作者: 张和明 E-mail:liu-wz19@mails.tsinghua.edu.cn;hmz@mail.tsinghua.edu.cn
作者简介:刘文正（1990-），女，博士生，研究方向为信息物理系统建模。Email：liu-wz19@mails.tsinghua.edu.cn
基金资助:
国家重点研发计划(2018YFB1701600)

A Cyber-physical Integrated Modeling Method Oriented for Motion Simulation of Complex Systems

Wenzheng Liu(), Heming Zhang()

Institute of Industrial Intelligence and Systems, Tsinghua University, Beijing 100090, China

Received:2022-02-09 Revised:2022-04-14 Online:2022-05-18 Published:2022-05-25
Contact: Heming Zhang E-mail:liu-wz19@mails.tsinghua.edu.cn;hmz@mail.tsinghua.edu.cn

摘要/Abstract

摘要：

传统运动仿真的虚拟建模缺少针对复杂系统中信息子系统与物理子系统的动态性融合建模。融合传统运动学虚拟建模与信息计算的优势，针对运动仿真的精度和实时性难以满足实际工业制造需求的问题，提出面向复杂系统运动仿真的信息物理融合建模方法，并以机械臂的运动学控制为仿真案例进行验证，解决了实际环境中机械臂的驱动与仿真环境虚拟机械臂运动不一致的问题。搭建了复杂系统运动仿真虚实映射平台，集成了虚拟建模环境CoppeliaSim，融合实际机器人的运动反馈，和虚实映射计算模型，确定工业机器人运动方程的唯一位姿解。实验结果表明本文提出的方法实现了工业机器人的虚实映射实时运动仿真。

关键词: 复杂系统建模, 运动仿真, 信息物理集成, 机械臂, 虚实运动映射

Abstract:

The traditional virtual modeling of motion simulation lacks the dynamic modeling of cyber subsystems and physical subsystems in complex systems. The advantages of the traditional kinematic virtual modeling and cyber calculation are combined, and aiming at the problem that the accuracy and real-time property of motion simulation cannot meet the actual industrial manufacturing requirements, a cyber physical integrated modeling method for the motion simulation of complex systems is proposed. The inconsistency between real robotic driving and virtual robot motion is solved, which is verified by a case study of mechanical arm motion control. A virtuality-reality mapping platform for complex system motion simulation is built, which integrates the modeling environment CoppeliaSim, together with actual robot feedback of motion and mapping model of simulated-actual robot motion, to obtain the unique pose solution of the motion equation. Experimental results show that the proposed method can realize real-time motion simulation of industrial robot.

Key words: complex system modeling, motion simulation, cyber-physical integration, robotic arms, kinematic mapping

中图分类号:

TP391.9

刘文正, 张和明. 面向复杂系统运动仿真的信息物理融合建模[J]. 系统仿真学报, 2022, 34(5): 954-963.

Wenzheng Liu, Heming Zhang. A Cyber-physical Integrated Modeling Method Oriented for Motion Simulation of Complex Systems[J]. Journal of System Simulation, 2022, 34(5): 954-963.

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参考文献 23

[1]	张霖, 周龙飞. 制造中的建模仿真技术[J]. 系统仿真学报, 2018, 30(6): 1997-2012.
	Zhang Lin, Zhou Longfei. Modeling & Simulation Technology in Manufacturing[J]. Journal of System Simulation, 2018, 30(6): 1997-2012.
[2]	李洪阳, 魏慕恒, 黄洁, 等. 信息物理系统技术综述[J]. 自动化学报, 2019, 45(1): 37-50.
	Li Hongyang, Wei Muheng, Huang Jie, et al. Survey on Cyber-physical Systems[J]. Acta Automatica Sinica, 2019, 45(1): 37-50.
[3]	孙子文, 张炎棋. 工业信息物理系统的攻击建模研究[J]. 控制与决策, 2019, 34(11): 2323-2329.
	Sun Ziwen, Zhang Yanqi. Research on Attack Modeling of Industrial Cyber Physical Systems[J]. Control and Decision, 2019, 34(11): 2323-2329.
[4]	李田, 苏盛, 杨洪明, 等. 电力信息物理系统的攻击行为与安全防护[J]. 电力系统自动化, 2017, 41(22): 162-167.
	Li Tian, Su Sheng, Yang Hongming, et al. Attacks and Cyber Security Defense in Cyber-Physical Power System[J]. Automation of Electric Power Systems, 2017, 41(22): 162-167.
[5]	刘思峰, 方志耕, 朱建军, 等. 系统建模与仿真[M]. 北京: 科学出版社, 2012.
	Liu Sifeng, Fang Zhigeng, Zhu Jianjun, et al. System Modeling and Simulation[M]. Beijing: Science press, 2012.
[6]	王长伟. 生产线快速建模与仿真系统关键技术研究[D]. 南京: 南京航空航天大学, 2007.
	Wang Changwei. Research on Key Technology of Production line Rapid Modeling and Simulation System[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2007.
[7]	张冰, 李欣, 万欣欣. 从数字孪生到数字工程建模仿真迈入新时代[J]. 系统仿真学报, 2019, 31(3): 369-376.
	Zhang Bing, Li Xin, Wan Xinxin. From Digital Twin to Digital Engineering Modeling and Simulation Entering a New Era[J]. Journal of System Simulation, 2019, 31(3): 369-376.
[8]	杨帆, 刘彦, 李仁发, 等. 一种基于数据驱动的CPS建模方法研究[J]. 计算机学报, 2016, 39(5): 961-972.
	Yang Fan, Liu Yan, Li Renfa, et al. A Modeling Method Research Based on Data in Cyber-Physical System[J]. Chinese Journal of Computers, 2016, 39(5): 961-972.
[9]	张磊, 孙会来. 基于无模型自适应控制算法的机械臂轨迹跟踪控制[J]. 天津科技, 2021, 48(4): 30-34.
	Zhang Lei, Sun Huilai. Trajectory Tracking Control of Manipulator Based on MFAC[J]. Tianjin Science & Technology, 2021, 48(4): 30-34.
[10]	Yilmaz L. On the Need for Contextualized Introspective Models to Improve Reuse and Composability of Defense Simulations[J]. The Journal of Defense Modeling and Simulation, 2004, 1(3): 141-151.
[11]	王维平, 周东祥, 李群, 等. 基于MDA的多层次框架式组合建模仿真方法研究[J]. 系统仿真学报, 2007, 19(19): 4358-4362.
	Wang Weiping, Zhou Dongxiang, Li Qun, et al. Multi-Level Framework for Composable Simulation Based on MDA[J]. Journal of System Simulation, 2007, 19(19): 4358-4362.
[12]	Zeigler B P, Zhang L. Service-Oriented Model Engineering and Simulation for System of Systems Engineering[M]. Berlin: Springer International Publishing, 2015: 19-44.
[13]	Fujimoto R M. Research Challenges in Parallel and Distributed Simulation[J]. ACM Transactions on Modeling and Computer Simulation (TOMACS), 2016, 26(4): 1-29.
[14]	熊嵩. 大型仿真模型体系的可重用性实现方法研究[J]. 现代导航, 2016, 7(2): 131-136.
	Xiong Song. Reusability Implementation Method of Large-Scale Simulation Model Architecture[J]. Modern Navigation, 2016, 7(2): 131-136.
[15]	李潭, 李伯虎, 柴旭东, 等. 复杂产品多学科虚拟样机元建模框架[J]. 计算机集成制造系统, 2011, 17(6): 1178-1186.
	Li Tian, Li Bohu, Chai Xudong, et al. Meta Modeling Framework for Complex Product Multidiscipline Virtual Prototyping[J]. Computer Integrated Manufacturing Systems, 2011, 17(6): 1178-1186.
[16]	Guo F, Cai H, Ceccarelli M, et al. Enhanced DH: An Improved Convention for Establishing a Robot Link Coordinate System Fixed on the Joint[J]. Industrial Robot: An International Journal, 2020, 47(2): 197-205.
[17]	杜楠, 谭亚新. 面向SaaS的LVC仿真试验中间件设计研究[J]. 系统仿真学报, 2021, 33(6): 1268-1276.
	Du Nan, Tan Yaxin. Design of LVC Simulation Test Middleware for SaaS[J]. Journal of System Simulation, 2021, 33(6): 1268-1276.
[18]	郭希铮, 游小杰, 徐从谦, 等. 大功率电力牵引控制系统硬件在回路实时仿真[J]. 电工技术学报, 2014, 27(4): 65-70.
	Guo Xizheng, You Xiaojie, Xu Congqian, et al. Simulation of Hardware in Loop for High-Power Electrical Traction System[J]. Transactions of China electrotechnical society, 2012, 27(4): 65-70.
[19]	傅成骏. 轨道交通车辆交流传动系统硬件在回路仿真技术进展[J]. 机车电传动, 2009, 3: 1-4.
	Fu Chengjun. Development of Hardware-in-Loop Simulation Technology for AC Drive Systems in Rail Vehicles[J]. Electric Drive for Locomotives, 2009, 3: 1-4.
[20]	吕升, 郭迎清, 孙浩. 航空发动机故障诊断装置硬件在环实时仿真平台[J]. 航空发动机, 2017, 43(3): 43-49.
	Lü Sheng, Guo Yingqing, Sun Hao. Hardware-in-Loop Real-time Simulation Platfom of Eault Diagnosis Device[J]. Aeroengine, 2017, 43(3): 43-49.
[21]	姚栋伟, 吴锋, 杨志家. 基于双伺服电机的电动助力转向器硬件在环仿真试验平台[J]. 浙江大学学报(工学版), 2009, 43(10): 1931-1934.
	Yao Dongwei, Wu Feng, Yang Zhijia. Hardware-in-Loop Simulation Test Platform of Electric Power Steering System Using Two Servo Motors[J]. Journal of Zhejiang University (Engineering Science), 2009, 43(10): 1931-1934.
[22]	Jeong S, Kwak Y, Lee W J. Software-in-the-Loop Simulation for Early-Stage Testing of Autosar Software Component[C]//2016 Eighth International Conference on Ubiquitous and Future Networks (ICUFN). Vienna, Austria: IEEE, 2016: 59-63.
[23]	Ayed M B, Zouari L, Abid M. Software in the Loop Simulation for Robot Manipulators[J]. Engineering, Technology & Applied Science Research, 2017, 7(5): 2017-2021.

面向复杂系统运动仿真的信息物理融合建模

A Cyber-physical Integrated Modeling Method Oriented for Motion Simulation of Complex Systems

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