摘要
通过对反应釜温度控制系统的分析讨论,针对传统控制中响应速度慢、自适应能力差等问题,本文设计了一种基于粒子群算法的模糊自适应PID控制器。该控制器通过对不同工况下控制器的比例因子和量化因子的实时优化来改善反应釜温度控制效果。仿真结果表明,粒子群优化模糊自适应PID控制器与传统的PID控制器和模糊控制器相比,系统动态特性和静态特性均得到了较大的提高,自适应能力显著增强。
Based on the analysis and discussion of the temperature control system of reactive kettle, a fuzzy adaptive PID controller based on particle swarm optimization （PSO） is designed to solve the problem of slow response and poor adaptive ability in traditional control. The controller through the real-time optimization of the controller scaling factors under different operating conditions and to improve the effect of temperature control of reactor kettle. The simulation results show that the dynamic performance and static performance of the system are improved greatly compared with the traditional PID controller and the fuzzy controller, and the adaptive ability is obviously enhanced.
作者
李国友
王红帅
张乐天
Li Guoyou Wang Hongshuai Zhang Letian(Key Laboratory of Industrial Computer Control Engineering, Yanshan University, Qinhuangdao 066004, Chin)
出处
《计算机与应用化学》
CAS
2017年第6期424-428,共5页
Computers and Applied Chemistry
基金
DCS控制苯乙烯仿真工厂-秦皇岛市科学技术研究与发展计划(201301B058)
国家自然科学基金资助项目(F2012203111)
河北省高等学校科学技术研究青年基金项目(2011139)
关键词
反应釜
温度控制
模糊PID控制
粒子群优化算法
reaction kettle
temperature control
fuzzy PID control
particle swarm optimization algorithm
