基于混沌理论的PID参数自整定锅炉汽包水位控制系统设计

锅炉汽包水位是工业蒸汽锅炉安全稳定运行的重要指标,目前水位控制普遍采用前馈串级三冲量控制器,控制效果与控制器PID参数选择关系很大,而常用的参数整定方法步骤繁琐,搜索效率较低,且不一定最优,控制效果常出现大的振荡和超调。本文利用混沌具有遍历性的特点,对基于Logistic映射的混沌搜索优化方法进行了改进,采用一类在有限区域范围内折叠次数无限的一维迭代混沌自映射,提出一种新的混沌PID优化参数方法。通过对汽包模型的仿真结果表明,该算法具有较高的搜索效率与搜索精度,能够实现PID参数的优化整定。

Design of a Water Level Control System for the Drum of a PID Parameter and Self-tuning Boiler Based on Chaotic Theory

The water level in a boiler drum is an important index for the safe and steady operation of an industrial steam boiler. Nowadays, for the water level control usually adopted are feed-forward cascade three-impulse controllers. The control effectiveness is heavily dependent on the proper selection of PID (proportional-integral-differential) parameters of the controller. However, the commonly used parameter-adjusting method involves complicated and tedious steps, resulting in a relatively low searching efficiency. Furthermore, the method is not always an optimized one and big oscillations and overshoots often occur to the control system. By making use of the ergodicity specific to the chaotic theory, one can improve the chaotic-searching optimization method based on Logistic mapping. Presented was a new chaotic PID-parameter optimization method by using one-dimensional iterative chaotic self-mapping which features infinite collapses in a finite region. The simulation results obtained by using the boiler drum models show that the relevant algorithm has a relatively high searching efficiency and accuracy, capable of realizing an optimized adjustment of PID parameters.