基于改进粒子群优化算法的溶解氧调控系统设计  

Design of dissolved oxygen control system based on improved particle swarm optimization algorithm

作　　者：曹守启[1] 葛照瑞 张铮 CAO Shouqi;GE Zhaorui;ZHANG Zheng(School of Engineering,Shanghai Ocean University,Shanghai 201306,China)

机构地区：[1]上海海洋大学工程学院,上海201306

出　　处：《传感器与微系统》2020年第6期113-115,共3页Transducer and Microsystem Technologies

基　　金：国家重点研发计划资助项目“蓝色粮仓科技创新”(2019YFD0900800);上海市科委2017年度“创新行动计划”资助项目(17050502000)。

摘　　要：针对循环水养殖系统中溶解氧调控大滞后、干扰多等问题进行研究。以STM32L单片机为主控芯片,利用溶解氧传感器、增氧机等建立溶解氧调控系统。根据模糊比例-积分-微分(PID)控制系统建立养殖塘溶解氧调控的数学模型,并引入粒子群算法进行模糊参数修正;为避免粒子群算法早熟、陷入局部最优,对原算法进行改进。通过MATLAB仿真和实验验证了所提方法的有效性。实验结果表明:与传统粒子群优化模糊PID控制和PID控制相比,采用改进粒子群优化算法的溶解氧调控系统响应速度更快,超调量减小,具有良好的控制效果。Aiming at the problem that control of dissolved oxygen in circulating water culture system is greatly delayed and there are much interference,dissolved oxygen control system is established by dissolved oxygen sensor and oxygen booster using STM32L micro-controller unit(MCU)main control chip.The mathematical model for dissolved oxygen regulation in culture pond is established according to the fuzzy proportional-integral-differential(PID)control system,and the particle swarm optimization(PSO)algorithm is introduced to correct the fuzzy parameters.The original algorithm is improved in order to avoid the early maturity of the particle swarm fall into the local optimum.The effectiveness of this method is verified by MATLAB simulation and experiment.Experimental results show that fuzzy PID control with traditional PSO,compared with the PID control,the dissolved oxygen control system with improved PSO algorithm has faster response speed and less overshoot,which has good control effect.

关 键 词：改进粒子群优化算法 模糊比例-积分-微分 溶解氧 循环水养殖 

分 类 号：TP233[自动化与计算机技术—检测技术与自动化装置] TP212[自动化与计算机技术—控制科学与工程]