首页|基于粒子群优化模糊PID控制的水厂加氯系统

基于粒子群优化模糊PID控制的水厂加氯系统

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水厂加氯过程具有非线性、大时滞等特点,采用传统的PID控制方式难以实现消毒剂精准投加.因此,以某采用次氯酸钠消毒系统的水厂为例,首先通过分析该水厂加氯系统工作原理,结合工程经验和运行数据确定了加氯过程的近似数学模型.然后综合使用粒子群优化算法、模糊控制算法和PID控制算法,设计了一种粒子群优化模糊PID控制器,并利用MATLAB软件搭建了粒子群优化模糊PID控制系统和传统PID控制系统的模型进行仿真验证,结果表明:相较于传统PID控制系统,粒子群优化模糊PID控制系统的超调量减少了 89.36%,调节时间减少了 46.63%,其抗干扰能力也更强,系统整体控制效果有了较大提升.最后使用基于粒子群优化的模糊PID控制法对水厂加氯控制系统进行改造,试运行后发现,新系统控制效果良好,出厂水游离氯值能够稳定在设定值附近.
Chlorination System of Water Plant Based on Particle Swarm Optimization Fuzzy PID Control
Because the chlorination process has characteristics of nonlinearity and large time delay in water plants,disinfectants can't be precisely dosed by traditional process identifier(PID)control methods.Therefore,taking a water plant that applied a sodium hypochlorite disinfection system as an example,the working principle of the chlo-rination system was analyzed,and an approximate mathematical model was determined by engineering experience and operating data.Then,a particle swarm optimization fuzzy PID controller was designed by particle swarm opti-mization algorithm,fuzzy control algorithm,and PID control algorithm.MATLAB software was used to build models of the particle swarm optimization fuzzy PID control system and the traditional PID control system for simulation ver-ification.The results showed that the overshoot of the particle swarm optimization fuzzy PID control system was re-duced by 89.36%,the adjustment time was reduced by 46.63%,the anti-interference ability was also stronger,and the overall control effect of the system had been greatly improved compared with the traditional PID control system.Finally,the method was used to modify the chlorination control system of the water plant.After trial operation,the new system had good control effect and the free chlorine value of the factory water was stable around the set value.

water plantchlorination systemfuzzy controlparticle swarm optimization algorithmprocess identifier(PID)control

刘晓艳、宋浪、汪恂、詹焕、谢世伟

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武汉科技大学城市建设学院,湖北武汉 430065

孝感市自来水有限公司,湖北孝感 432000

水厂 加氯系统 模糊控制 粒子群优化算法 PID控制

国家自然科学基金

51808415

2024

市政技术
中国市政工程协会 北京市政路桥股份有限公司 北京市政建设集团有限责任公司 北京市市政工程研究院

市政技术

影响因子:0.385
ISSN:1009-7767
年,卷(期):2024.42(3)
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