基于混沌粒子群优化算法的反应釜温度预测控制研究

Research on Predictive Control of Reactor Temperature Based on Chaotic Particle Swarm Optimization Algorithm

反应釜作为化工行业核心的生产容器,其温度控制优化在化工生产领域中具有重要作用。针对反应釜温度控制难的问题,提出了一种基于Tent映射的混沌粒子群优化(CPSO)算法优化动态矩阵控制(DMC)-比例积分微分(PID)的反应釜温度预测控制策略。由于DMC很难选取较优的参数,利用Tent映射的CPSO算法提高动态矩阵参数寻优的速度。通过试验,以及与常规PID、DMC-PID控制对比分析,基于Tent映射的CPSO-DMC-PID串级控制对温度控制系统有较好的控制精度和响应速度,可大幅缩小超调量。该控制策略对反应釜温度预测控制研究具有一定的参考意义。

As a core production vessel in chemical industry,the optimization of temperature control of reactor plays an important role in chemical production field.Aiming at the difficult problem of reactor temperature control,a reactor temperature predictive control strategy based on Tent mapping chaotic particle swarm optimization(CPSO) algorithm to optimize dynamic matrix control(DMC)-proportional integral differential(PID) is proposed.Since it is difficult to select better parameters for DMC,the CPSO algorithm with Tent mapping is utilized to improve the speed of dynamic matrix parameter optimization.Through tests,and the comparison and analysis with the conventional PID and DMC-PID control,the CPSO-DMC-PID series control based on the Tent mapping has better control accuracy and response speed for the temperature control system and can reduce the amount of overshooting significantly.The control strategy has certain reference significance for the predictive control research of reactor temperature.