蚁群算法在油库发油PID控制中的应用

针对目前油库定量发油过程具有非线性、滞后性等特点,常规PID控制难以达到预期的控制精度,提出一种蚁群算法优化PID参数的控制方案。在PID发油控制系统的基础上引入蚁群算法,通过蚁群迭代寻优的方式优化PID控制参数,从而实现油库发油的稳定性。在控制系统中,采用S7-1200 PLC为控制器,通过SCL语言实现算法,PID参数基于蚁群算法动态优化。实验表明,所提出的方法较PID参数Z-N整定法更具实用性和有效性,超调量减少58%,能够使发油控制更加稳定。

Application of Ant Colony Algorithm in PID Control of Oil Depot Delivery

In view of the non-linearity and hysteresis of quantitative oil depot delivery process,it is difficult for conventional PID control to achieve the desired control precision.Inspired by this,a control scheme based on the ant colony algorithm is proposed to optimize PID parameters.Integrated into the control scheme on the basis of PID control system,an ant colony algorithm is used to optimize PID control parameters so as to guarantee stable oil depot delivery.In this control system,S7-1200 PLC is adopted as the controller,the algorithm is implemented through SCL language,and the PID parameters are optimized dynamically based on the ant colony algorithm.The experiment shows that the proposed method is more practical and effective than Z-N method.The overshoot is reduced by 58%,which can make the oil control more stable.