期刊文献+

基于改进混合蛙跳算法的电渣重熔过程多变量PID控制器设计 被引量:14

Design of multivariable PID controller of electroslag remelting process based on improved shuffled frog leaping algorithm
原文传递
导出
摘要 根据电渣重熔过程的工艺特点和数学模型,提出了基于改进混合蛙跳算法(ISFLA)的多变量参数自整定PID控制策略.提出一种新的蛙跳规则,用以增强SFLA的局部搜索能力.该规则主要通过模拟青蛙的感知和运动的不确定性来动态随机地调整青蛙的局部搜索空间和步长,以防止SFLA算法过早收敛,提高算法的搜索效率.仿真结果和工业应用实验均表明了所提出控制方法的可行性和有效性. Based on the technique features and mathematical model of electroslag remelting(ESR) process,a multivariable self-tuning PID controller tuned optimally by an improved shuffled frog leaping algorithm(ISFLA) is proposed to control the two-input-two-output(TITO) ESR process.A new frog leaping rule is proposed to enhance the SFLA's local search capabilities,which adjusts the frog local search space and the step of each flog's jump dynamically and randomly by emulating frog's perception and action uncertainties in order to prevent premature convergence and improve the search efficiency of SFLA.The simulation results and industrial application tests show the feasibility and effectiveness of the proposed control method.
出处 《控制与决策》 EI CSCD 北大核心 2011年第11期1731-1734,共4页 Control and Decision
基金 中国博士后科学基金面上项目(20110491510) 辽宁省教育厅创新团队基金项目(2008T091)
关键词 电渣重熔过程 多变量系统 PID控制器 混合蛙跳算法 electroslag remelting process multivariable system PID controller shuffled frog leaping algorithm
  • 相关文献

参考文献8

  • 1赵丽丽,宋锦春,刘喜海,柳洪义.基于遗传算法的电渣重熔过程智能控制研究[J].机械与电子,2008,26(5):16-19. 被引量:5
  • 2任伟,郑险峰,姜立新,胡杰,印云志.电渣炉电极调节系统的模糊自适应PID控制[J].冶金自动化,2006,30(1):15-18. 被引量:15
  • 3Chanchal D, Rajani K M. An improved auto-tuning scheme for PID controllers[J]. ISA Transactions, 2009, 48(4): 396- 409.
  • 4Cheng C H, Cheng P G, Xie M J. Current sharing of paralleled DC-DC converters using GA-based PID controllers[J]. Expert Systems with Applications, 2010, 37(1): 733-740.
  • 5Chan W D, Shih S P. PID controller design of nonlinear systems using an improved particle swarm optimization approach[J]. Communications in Nonlinear Science and Numerical Simulation, 2010, 15(11): 3632-3639.
  • 6Eusuff M M, Lansey K E. Optimization of water distribution network design using the shuffled frog leaping algorithm[J]. J of Water Resources Planning and Management, 2003, 129(3): 210-225.
  • 7朱光宇.模因内三角概率选择混合蛙跳算法[J].计算机集成制造系统,2009,15(10):1979-1985. 被引量:15
  • 8Huynh T H. A modified shuffled frog leaping algorithm for optimal tuning of multivariable PID controllers[C]. IEEE Int Conf on Industrial Technology. Perth: IEEE Press, 2008: 1-6.

二级参考文献26

  • 1伍楷舜,郝井华,刘民,吴澄.表面贴装过程调度问题的粒子群优化算法[J].控制工程,2007,14(2):132-134. 被引量:5
  • 2李宛州,王京春.工业过程中一类时变模型的建立与控制方法研究[J].自动化学报,2006,32(1):120-124. 被引量:2
  • 3薛亚丽,李东海,吕崇德.基于遗传算法的机炉协调系统PID控制器优化[J].热能动力工程,2006,21(1):80-83. 被引量:10
  • 4陈世哲,刘国栋,浦欣,浦昭邦,胡涛,刘宛予.基于优势遗传的自适应遗传算法[J].哈尔滨工业大学学报,2007,39(7):1021-1024. 被引量:31
  • 5王英章.高精高速微孔PCB数控钻床关键技术的研究与应用[D].重庆:重庆大学,2005.
  • 6AYOB M, KENDALL G. A survey of surface mount device placement machine optimization: machine classification [ J ]. European Journal of Operational Research, 2008, 186 ( 3 ) : 893-914.
  • 7LI Shaoyuan, HU Chaofang, TIAN Fuhou. Enhancing optimal feeder assignment of the multi-head surface mounting machine using genetic algorithms[J]. Applied Soft Computing, 2008,8(1):522 529.
  • 8KUMAR R, LI H. Integer programming approach to printed circuit board assembly time optimization[J]. IEEE Transactions on Components Packaging and Manufacturing Technology, 1995,18(4) : 720-727.
  • 9ALTINKEMER K, KAZAZ B, KOKSALAN M, et al. Optimization of printed circuit board manufacturing: integrated modeling and algorithms[J]. European Journal of Operational Research,2000,124(2) :409-421.
  • 10KIMBERLY P E, FERNANDO J V, JOHN E K. Optimizing the performance of a surface mount placement machine[J]. IEEE Transactions on Electronic Packaging Manufacturing, 2001,24(3): 160-170.

共引文献31

同被引文献136

引证文献14

二级引证文献46

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