温控系统的智能优化方法研究与设计  

Research and design of intelligent optimization method on temperature control system

作　　者：李学忠[1] 戴钧[1] 柳毅[2] 

机构地区：[1]杭州电子科技大学计算机学院,浙江杭州310018 [2]杭州电子科技大学管理科学与信息工程研究所,浙江杭州310018

出　　处：《机电工程》2014年第7期955-958,共4页Journal of Mechanical & Electrical Engineering

基　　金：浙江省重点科技创新团队项目(2010R50008)

摘　　要：针对传统PID温控系统存在的调节时间长、精度低的问题,对温控系统的控制算法、执行机构、反馈量等方面进行了研究,提出了一种温控系统的智能优化方法。采用增量式PID算法对执行机构进行控制,用遗传算法优化最小输出量,达到了平滑PID输出的效果。在控制过程中将最小输出量作为遗传因子,采用绝对误差的一阶矩型累加和的倒数为适应度函数,进行了最小输出量的在线优化及寻找最优解,减少了执行机构的振荡次数。设计了多线程控制方式,控制线程实现了控制逻辑,PID线程实现了精确控制,优化了线程实现最小输出量的优化,通过DITT调度算法来协调多线程,提高了系统利用率。研究结果表明,该智能优化方法已成功地运用在炉温控制系统中,系统的动态性能得到了提高,增强了系统的快速性,达到了控制效果。Aiming at solving the problem of long adjustment time and low precision in traditional PID temperature control system, the control algorithm of the temperature control system, actuator and feedback quantity were reached, temperature control system of intelligent optimization method was proposed. The incremental PID algorithm was used to control the actuator. Genetic algorithm optimization was used for the minimum output, smooth PID output effect was achived. In the process of PID control, the minimum output was used as the genetic factor, the reciprocal of integrated time absolute error was adopted. Thus minimum output on line was set and the oscillation frequency of the actuator was reduced. Muhithreaded control mode was designed, control logic of control threading was realized, accuracy control of PID threading was achieved and optimization of parameter in optimizing threading was realized. By DITT scheduling algorithm, muhithreading control was coor- dinated to improved the system utilization. The results indicate that intelligent optimization method is successfully used in the furnace temperature control system, improves the dynamic performance, enhances the rapidity of the system, ensures the control effect.

关 键 词：智能优化 PID 遗传算法 多线程 炉窑 

分 类 号：TP273.2[自动化与计算机技术—检测技术与自动化装置]