双容水箱基于QPSO算法的PID控制研究  

Research on PID Control of Double Tank Based on QPSO Algorithm

作　　者：李磊 李俊红[1] 顾菊平[1] 华亮[1] LI Lei;LI Jun-hong;GU Ju-ping;HUA Liang(School of Electrical Engineering,Nantong University,Nantong 226019,China)

机构地区：[1]南通大学电气工程学院,江苏南通226019

出　　处：《控制工程》2021年第8期1553-1558,共6页Control Engineering of China

基　　金：国家自然科学基金资助项目(61973176,61973178);江苏省自然科学基金资助项目(BK20181457);江苏省高校自然科学基金资助项目(20KJA470002);江苏省六大人才高峰项目(XYDXX-038)。

摘　　要：双容水箱液位系统是典型的非线性、时延系统,以CS4000装置为研究对象,通过机理法和测试法建立其数学模型。粒子群优化算法是模拟鸟类群体行为的智能算法,参数设置较少,收敛性较好,但寻优过程易陷入局部最优解。为此,提出了量子行为粒子群优化算法。针对常规比例积分微分(proportional-integral-derivative,PID)控制器在处理时延、非线性对象方面的不足,提出了基于量子行为粒子群优化算法的PID控制器,并将该控制器用于双容水箱液位系统。结果表明,相比于常规PID控制器和粒子群优化算法,基于量子行为粒子群优化算法的PID控制器具有更好的控制效果。Double tank liquid level system is a typical nonlinear and time-delay system.Taking the CS4000 device as the research object,its mathematical model is established by the mechanism method and test method.Particle swarm optimization algorithm is an intelligent algorithm that simulates the behavior of bird swarm.It has fewer parameters and better convergence,but it is easy to fall into the local optimal solution in the optimization process.Therefore,quantum-behaved particle swarm optimization algorithm is proposed.Aiming at the shortcomings of conventional proportional-integral-derivative(PID)controller in processing time-delay and nonlinear objects,the PID controller based on quantum-behaved particle swarm optimization algorithm is proposed.The controller is applied to the double tank liquid level system.The results show that compared with the conventional PID controller and particle swarm optimization algorithm,the PID controller based on quantum-behaved particle swarm optimization algorithm has better control effect.

关 键 词：双容水箱 粒子群优化算法 量子行为粒子群优化算法 PID控制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]