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Design of multivariable PID controller using DE-PSO

机译:基于DE-PSO的多变量PID控制器设计

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This paper presents design of multivariable PID controller using a novel method differential evolution (DE)-based particle swarm optimisation (PSO) for two-input two-output (TITO) processes and its performance compare with evolutionary algorithms (EAs) like DE and modified PSO methods. In the proposed DE-PSO method, preliminary DE is applied on the random generated population then PSO is used to update the position and velocity of the particles. To validate the effectiveness of the proposed DE-PSO method, two different industrial processes and real time experiment on four tank level control system is considered. Simulation results show that DE-based PSO is better than both MPSO and DE in terms of getting global optimum in less iterations and avoiding premature convergence.
机译:本文提出了一种基于新颖方法的基于差分进化(DE)的粒子群优化(PSO)的多变量PID控制器设计,用于两输入两输出(TITO)过程,并且其性能与DE和改进的进化算法(EA)进行了比较PSO方法。在提出的DE-PSO方法中,将初步DE应用于随机生成的总体,然后使用PSO更新粒子的位置和速度。为了验证所提出的DE-PSO方法的有效性,考虑了两个不同的工业过程以及在四罐液位控制系统上的实时实验。仿真结果表明,基于DE的PSO在以更少的迭代获得全局最优并避免过早收敛方面优于MPSO和DE。

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