期刊文献+

纳卫星主动温控系统建模与仿真 被引量:2

Modeling and Simulation of Nano-satellite's Active Themal Control System
下载PDF
导出
摘要 纳卫星运行于复杂空间热环境中,各种热量干扰、轨道外热流波动和舱内热源的散热都会影响整个星体的温度系统,因此制定合理的温度控制策略尤为重要。在纳卫星动态特性平衡方程基础上建立了主动热控系统模型。分别采用常规PID控制方法与模糊控制方法,对纳卫星温度控制系统进行了仿真研究。仿真结果表明,PID控制能消除稳态误差,满足一定的控温要求,但超调大,过渡时间长;模糊控制则能实时跟踪纳卫星温度变化,较快地达到控温目标值,虽然无法消除静态误差,但其综合控制效果比PID要好。 When Nano-satellite orbits in the outer space,different kinds of heat disturbance,orbit external heat flow fluctuation and instrument's heat radiation will influence its temperature system,so it's important to make a reasonable thermal control strategy.A model of Nano-satellite's active thermal control system was established based on the equations of dynamic characteristics.Simulation of temperature control system in the satellite was made by using PID and fuzzy control methods.The results show that PID control can eliminate steady-state error and satisfy the temperature demands,but the overshoot is big,transitional time is long.On the other side,fuzzy control can follow the change of the Nano-satellite's temperature,reach the target value swiftly.Although the fuzzy control can't eliminate steady-state error,its synthetic control quality is better than that of PID control.
作者 杨娟 李运泽
出处 《计算机仿真》 CSCD 2008年第7期58-61,共4页 Computer Simulation
基金 国家自然科学基金资助项目(50506003)
关键词 纳卫星 主动温度控制 模糊控制 仿真 Nano-satellite Active temperature control Fuzzy control Simulation
  • 相关文献

参考文献5

  • 1M R Butcher. Spacecraft thermal design: Particular problems with small satellites[J]. Journal of Aerospace Engineering, 1999, 213 (4) : 245 -253.
  • 2M Seven, K Manfred, L Norbert. Nanosatellite and microsystem technology capabilitis, limitation and applications[ J]. Acta Astron, 2005,39(4) :799 -808.
  • 3Volodymyr Baturkin. Micro - satellites thermal control concepts [J]. Acta Astronautica, 2005, 56:161 - 170.
  • 4向四桂,沈怀荣.微型航天器热控系统设计[J].装备指挥技术学院学报,2002,13(5):44-46. 被引量:5
  • 5朱娟萍,侯忠生,熊丹.神经网络控制、无模型控制PID控制仿真比较[J].系统仿真学报,2005,17(3):751-754. 被引量:9

二级参考文献8

  • 1Narendra K S, Parthasarathy K. Identification and Control of Dynamic Systems Using Neural Networks [J]. IEEE Trans. neural networks, 1990, 1(1): 4-27.
  • 2Narendra K S. Neural Networks for Control: Theory and Practice [A]. Proc. of The IEEE [C]. 1996, 84(10): 1385-1406.
  • 3Cabrera J B D, Narendra K S. Issues in the Application of Neural Networks for Tracking Based on Inverse Control [J]. IEEE Trans., automatic control, 1999, 44(11): 2007-2027.
  • 4Narendra K S, Mukhopadhyay S. Adaptive Control Using Neural Networks and Approximate Models [J]. IEEE Transactions on Neural Networks, 1997, 8(3): 475-485.
  • 5侯忠生.非参数模型及其自适应控制理论[M].北京:科学出版社,1998..
  • 6Tan K K, Lee T H, Huang S N, Leu F M. Adaptive Predictive Control of a Class of SISO Nonlinear Systems [J]. Dynamics and Control, 2001, 11(2): 151-174.
  • 7Tan K K, Adaptive Predictive PI Control of a Class of SISO Systems [A]. Proc. of ACC [C]. San Diego, California, 1999: 3848-3852.
  • 8Chen F C. Back-Propagation Neural Networks for Nonlinear Self- Tuning Adaptive Control [J]. IEEE control Systems Magazine, 1990, 4(1): 44-48.

共引文献12

同被引文献15

引证文献2

二级引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部