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Optimum Design of PID Controller Parameters by Improved Particle Swarm Optimization Algorithm

机译:改进的粒子群优化算法优化PID控制器参数。

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To avoid the slow convergence and the premature problem of basic particle swarm optimization algorithm (basic PSO), an improved particle swarm optimization algorithm (IPSO) was presented to used for optimizing PID controller parameters. On the basic of the basic PSO with contraction factor, the IPSO with mutation probability was proposed to get a good population diversity and to avoid basic PSO getting into local best result. In order to gain satisfied transient process dynamic characteristics, Integral Time Absolute Error (ITAE) is adopted as the fitness function for parameter selection. The IPSO applied to optimizing PID controller parameters are much better than those of basic PSO.
机译:为了避免基本粒子群优化算法(基本PSO)收敛速度慢和过早的问题,提出了一种改进的粒子群优化算法(IPSO)来优化PID控制器参数。在具有收缩因子的基本PSO的基础上,提出了具有突变概率的IPSO,以实现良好的种群多样性,避免基本PSO陷入局部最佳状态。为了获得令人满意的瞬态过程动态特性,采用积分时间绝对误差(ITAE)作为参数选择的适应度函数。用于优化PID控制器参数的IPSO比基本PSO的要好得多。

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