|本期目录/Table of Contents|

[1]郭松林,王光辉.基于人工蜂群算法优化采煤机伺服系统PID参数[J].工业仪表与自动化装置,2018,(02):29-32.[doi:1000-0682（2018）02-0000-00]
　GUO Songlin,WANG Guanghui.Optimization of PID parameters of hydraulic servo system based on artificial bee colony algorithm[J].Industrial Instrumentation & Automation,2018,(02):29-32.[doi:1000-0682（2018）02-0000-00]
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基于人工蜂群算法优化采煤机伺服系统PID参数

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2018年02期
页码:
29-32
栏目:
出版日期:
2018-04-15

文章信息/Info

Title:
Optimization of PID parameters of hydraulic servo system based on artificial bee colony algorithm
作者:
郭松林; 王光辉
黑龙江科技大学 电气与控制工程学院，哈尔滨 150022
Author(s):
GUO Songlin; WANG Guanghui
(School of Electrical &Control Engineering ,Heilongjiang University of Science & Technology,Harbin 150022,China)
关键词:
人工蜂群算法; PID控制器; 粒子群优化算法; 遗传算法
Keywords:
artificial bee colony algorithm;  PID controller;  particle swarm optimization algorithm;  genetic algorithm
分类号:
TP18
DOI:
1000-0682（2018）02-0000-00
文献标志码:
A
摘要:
针对采煤机电液伺服系统中PID控制器的参数寻优问题，利用人工蜂群算法来优化PID参数。人工蜂群算法通过模拟群峰寻找花蜜的过程，将误差绝对值和控制输入平方项的时间积分作为优化目标，经过迭代寻优计算得到系统最优控制量。通过典型函数测试，对比分析遗传算法和粒子群优化算法，人工蜂群算法具有较好的全局收敛能力。结果表明: 人工蜂群算法用于采煤机电液伺服系统的参数调节，比遗传算法和粒子群优化算法收敛速度快，超调量小，具有更好的动态响应性能，验证了该方案的可行性和有效性。
Abstract:
This paper aims to address the parameter optimization of PID controller in electro-hydraulic servo system of coal mining machine, and proposes to optimize the PID parameters by artificial bee colony algorithm(ABC). The artificial bee colony algorithm was viewed as a process of seeking nectar by simulating peaks，the integration for absolute error and the square of control input were used as optimization goals，and the optimal control quantity was calculated through iterative optimization. Through the typical function test, it has better global convergence ability by contrasting genetic algorithm and particle swarm optimization algorithm. The simulation results show that this method, applied to the parameter adjustment of hydraulic servo system of coal miner ,has better dynamic response performance than genetic algorithm and particle swarm optimization algorithm, which verifies the feasibility and effectiveness of the scheme.

参考文献/References:

[1] 王亚刚,许晓鸣,邵惠鹤.基于Ziegler-Nichols率响应方法的自适应PID控制[J].控制工程,2012(4):607-613.

[2] 曹志松,朴英.基于混合遗传算法的航空发动机PID 控制参数寻优[J].航空动力学报,2007,22(9):1588-1592.
[3] ABDEL B. Genetic fuzzy self-tuning PID controllers for antilock braking systems[J].Engineering Application of Artificial Intelligent,2010,23(7):1041-1025.
[4] HUNG M, LIN J, YAN J.Optimal PID control design for synchronization of delayed discrete chaotic systems[J]. Chaos Solitons & Fractals, 2008,35(4):781-785.
[5] 余胜威,曹中清.基于人群搜索算法的PID控制器参数优化[J].计算机仿真,2014,31(9):347-350.
[6] 宁爱平,张雪英.人工蜂群算法的收敛性分析[J].控制与决策,2013,28(10):1554-1558.

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备注/Memo

备注/Memo:
收稿日期：2017-09-19
基金项目：国家重大科学仪器设备开发专项（2012YQ150213）
作者简介：郭松林（1963），男，黑龙江省黑河人，教授，硕士，研究方向为数字信号处理，电子测量及供电检测技术。E-mail:gsl63@163.com
更新日期/Last Update: 2018-04-15