期刊文献+

散热器试验台送风系统规则自提取模糊控制试验

Self-Abstracting Rule Fuzzy Control Experiment of Supply Air System in a Radiator Performance Rig
下载PDF
导出
摘要 提出了环境试验室送风系统规则自提取模糊控制方法,试验研究了基于送风加热器调节的送风温度与测试室温度的模糊控制和比例积分(PI)控制效果.试验结果表明,对于无滞后环节的送风加热器-送风温度控制回路,传统PI控制方法具有较好的控制性能,收敛速度快;基本模糊控制方法收敛较慢,存在稳态误差;规则自提取模糊控制方法超调大,但收敛速度加快,稳态误差减小.对于具有滞后环节的送风加热器-测试室温度控制回路,规则自提取模糊控制方法超调小、稳态误差小、控制效果最好.可见,对于无滞后环节的被控过程,采用PI控制方法即可满足要求;而规则自提取模糊控制方法非常适用于具有大滞后环节的过程控制. A self-abstracting rule fuzzy control (SARFC)method for supply air system in a radiator performance rig has been put forward and fuzzy control experiments and proportion integration (PI) control experiments for the controlled loops of both supply air temperature and testing room air temperature have been carried out based on adjustment by the electrical heater set in the supply air system. Two types of fuzzy control have been experimented,i.e, basic fuzzy control and SARFC with zero initial control rules. Experiment results indicate that for the control loop of supply air electrical heater and supply air temperature without time delay,PI control has a better control performance and a higher constringency speed than the fuzzy control,basic fuzzy control has a lower constringency speed and a stable error,and SARFC has a higher overshoot, higher constringency speed and smaller stable error. For the control loop of supply air electrical heater and testing room air temperature with time delay,SARFC has a satisfactory control performance with a lowet, ershoot and smaller stable error than the basic fuzzy control and PI control. According to the experiments,SARFC is particularly suitable for the control process with a large time delay while PI is a good candidate for the control process without time delay.
出处 《天津大学学报》 EI CAS CSCD 北大核心 2010年第1期43-49,共7页 Journal of Tianjin University(Science and Technology)
基金 "十一五"国家科技支撑计划资助项目(2006BAJ01A09 2008BAJ12B05) 国家自然科学基金资助项目(50578049)
关键词 散热器试验台 送风系统 自组织模糊控制 规则自提取 radiator performance rig supply air system self-organizing fuzzy control self-abstra^ing rule
  • 相关文献

参考文献11

  • 1Tobi T,Hanafusa T. A practical application of filzzy control for an air-conditioning system [J]. International Journal of Approximate Reasoning, 1991,5 (3) : 331-348.
  • 2Albert T P ,Chart W L ,Chow T T ,et al. A neural network based identifier/controller for modem HVAC control [J]. ASHRAE Transactions, 1995,101 (2) : 14-31.
  • 3Huang S ,Nelson R M. Rule development and adjustment strategies of a fuzzy logic controller for an HVAC system (Part I ): Analysis [J]. ASHRAE Transactions, 1994, 100 (2) :841-850.
  • 4Huang S ,Nelson R M. Rule development and adjustment strategies of a fuzzy logic controller for an HVAC system (Part II) : Experiment [J]. ASHRAE Transactions, 1994, 100(2) :851-856.
  • 5Huang S ,Nelson R M. Development of a self-tuning fuzzy logic controller [J]. ASHRAE Transactions, 1999, 105 (1) :206-213.
  • 6Cox E. Adaptive fuzzy system [J]. IEEE Spectrum, 1993,30 (2) : 27-31.
  • 7Nie J,Linkens D A. Learning control using fuzzified self- organizing radial basis function network[J]. IEEE Trans on Fuzzy Systems, 1993,1 (4) :280-287.
  • 8叶其革,吴捷.一种自组织模糊神经网络控制器[J].控制与决策,1998,13(6):694-696. 被引量:14
  • 9Wang Liang,Yen J. Extracting fuzzy rules for system modeling using a hybrid of genetic algorithms and Kalman filter [J]. Fuzzy Sets and Systems,1999,101 (3) : 353-362.
  • 10Chen S M,Chen Y C. Automatically constructing membership functions and generating fuzzy rules using genetic algorithms [J]. Cybernetics and Systems ,2002, 33 (8) :841-862.

二级参考文献6

共引文献36

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