First application of symbiotic organisms search algorithm to off-line optimization of PI parameters for DSP-based DC motor drives
First application of symbiotic organisms search algorithm to off-line optimization of PI parameters for DSP-based DC motor drives
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DOI：
10.1007/s00521-017-3256-5
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发表时间：
2018-09-01
影响因子：
6
通讯作者：
Ozturk, Nihat
中科院分区：
文献类型：
--
作者：
Celik, Emre;Ozturk, Nihat
为了增强直流电流驱动器的性能和动力学，本文提出了一种基于最近引入强大的共生生物搜索（SOS）算法的新替代方案，用于调整比例积分参数。在模仿生态系统中生物体中看到的共生行为时，SOS具有重要的特征，因此它不需要调整参数，并且通过有效的三个阶段，其实现非常容易。在精确准备好的仿真软件中获得K（p）-K（i）对的优化值之后，它们将实时使用。通过使用TMS320F28335的DSP管理直流电动机速度控制系统，几个模拟和实验结果证实了我们的提案的性能以及与粒子群优化（PSO），遗传算法（GA）和Ziegler-Nichols的比较以及比较。 （Z-N）调整方法。结果明确表明，SOS是相关驱动系统的更好跟踪性能和负载干扰拒绝能力的先驱，其次是PSO，GA和Z-N方法。由于SOS获得的收益比其他应用方法获得的收益更具性能，因此实现了这一目标。
To enhance the performance and dynamics of a direct current (DC) motor drive, this paper proposes a new alternative based on recently introduced powerful symbiotic organisms search (SOS) algorithm for tuning proportional integral parameters. While imitating the symbiotic behavior that is seen among organisms in an ecosystem, SOS has important features such that it does not require tuning parameters, and its implementation is very easy with efficient three phases. After obtaining the optimized values of K (p) - K (i) pair within the accurately prepared simulation software, they are used in real time. By managing the DC motor speed-controlled system with DSP of TMS320F28335, several simulations and experimental results confirming the performance of our proposal are presented along with comparisons against those of particle swarm optimization (PSO), genetic algorithm (GA), and Ziegler-Nichols (Z-N) tuning method. Results explicitly show that SOS is the pioneer in yielding better tracking performance and load disturbance rejection capability of the concerned drive system, which is followed by PSO, GA, and Z-N method, respectively. This has been achieved due to the fact that the gains obtained by SOS are more performant than those obtained by other applied methods.