基于模糊粒子群PID算法的温控系统研究
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南通大学信息科学技术学院,南通 226000

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TP13

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江苏省高等学校自然科学研究重大项目(19KJ320004)


Research on Temperature Control System Based on Fuzzy Particle Swarm PID Algorithm
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School of Information Science and Technology, Nantong University, Nantong 226000, China

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    摘要:

    针对电容器热压机温度控制系统存在滞后大、非线性的问题,分析了电容器热压机温度控制系统的原理,建立了温度控制系统的数学模型。通过对传统PID控制算法、粒子群算法和模糊控制算法的研究,提出了一种将模糊粒子群PID算法应用于温度控制系统的方案。用MATLAB对温控系统进行仿真,得出采用传统PID控制算法的温控系统的调节时间和超调量分别为66s和58.173%,而采用模糊粒子群PID算法的温控系统的调节时间和超调量为分别是34s和6.295%。研究结果表明,基于模糊粒子群PID算法的电容器热压机温度控制系统在调节时间、超调量和抗干扰能力等方面均优于传统PID控制算法。

    Abstract:

    For the temperature control system of the capacitor hot press, there are problems such as large lag and nonlinearity. The principle of the temperature control system of the capacitor hot press is analyzed and the mathematical model of the temperature control system is established. Through the research of traditional PID control algorithm, particle swarm algorithm and fuzzy control algorithm, a scheme of applying fuzzy particle swarm PID algorithm to temperature control system is proposed. Use MATLAB to simulate the temperature control system. The adjustment time and overshoot of the temperature control system using the traditional PID control algorithm are 66s and 58.173%, respectively. The temperature control system using the fuzzy particle swarm PID algorithm has an adjustment time and overshoot of 34s and 6.295%, respectively. The research results show that the temperature control system of the capacitor hot press based on the fuzzy particle swarm PID algorithm is superior to the traditional PID control algorithm in terms of adjustment time, overshoot and anti-interference ability.

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张 峰,王 强.基于模糊粒子群PID算法的温控系统研究[J].电子测量技术,2022,45(13):109-114

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  • 在线发布日期: 2024-04-11
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