Bacterial Swarm Foraging Optimization Algorithm and Its Application in Optimization of PID Parameters

China Mechanical Engineering ›› 2014, Vol. 25 ›› Issue (1): 59-64.

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Bacterial Swarm Foraging Optimization Algorithm and Its Application in Optimization of PID Parameters

Chen Dongning1,2;Zhang Guofeng1,2;Yao Chengyu3;Zhang Ruixing1,2

1.Hebei Provincial Key Lab of Heavy Machinery Fluid Power Transmission and Control，Yanshan University，Qinhuangdao，Hebei,066004
2.Key Lab of Advanced Forging & Stamping Technology and Science，Ministry of Education，Yanshan University， Qinhuangdao，Hebei,066004
3.Key Lab of Industrial Computer Control Engineering of Hebei Province，Yanshan University，Qinhuangdao，Hebei,066004

Online:2014-01-10 Published:2014-01-14
Supported by:
National Natural Science Foundation of China（No. 50905154）;Hebei Provincial Natural Science Foundation of China（No. E2012203015）;Hebei Provincial Scientific Research Project of Ministry of Education of China（No. ZH2012062）;Key Technology R&D Program of Qinhuangdao （No. 2012021A078）

细菌群觅食优化算法及PID参数优化应用

陈东宁1,2;张国峰1,2;姚成玉3;张瑞星1,2

1.燕山大学河北省重型机械流体动力传输与控制实验室，秦皇岛，066004
2.燕山大学先进锻压成形技术与科学教育部重点实验室，秦皇岛，066004
3.燕山大学河北省工业计算机控制工程重点实验室，秦皇岛，066004

基金资助:
国家自然科学基金资助项目(50905154)；河北省自然科学基金资助项目(E2012203015)；河北省教育厅资助科研项目(ZH2012062)；秦皇岛市科技支撑计划资助项目(2012021A078)

Abstract

Abstract:

To overcome the shortages of slow convergence in bacterial foraging(BF) algorithm and premature in particle swarm optimization(PSO) algorithm, a bacterial swarm foraging optimization(BSFO) algorithm was proposed. The velocity updating formula in PSO was used to replace the direction vector of position formula in BF algorithm, therefore each bacterium had the ability of perceiving the position of the neighborhood bacteria and moving to the historical best position of the whole swarm. The optimal results of benchmark test functions show that the BSFO algorithm has better performance for most of the functions. Besides, the BSFO algorithm was applied to the simulation of optimization of the PID controller's parameters, which was used in an electro-hydraulic position servo system of material testing machine, and the PID control system has good control performance.

Key words: bacterial swarm foraging optimization algorithm, particle swarm optimization algorithm, bacterial foraging algorithm, PID controller, electro-hydraulic position servo system

摘要：

针对细菌觅食(BF)算法收敛速度慢和粒子群优化(PSO)算法早熟的缺点，提出了一种细菌群觅食优化(BSFO)算法。将PSO算法中粒子速度的更新公式替代BF算法位置公式中的方向向量，使细菌在优化过程中具备感应周围细菌位置并向细菌群体历史最优位置游动的能力。Benchmark函数的测试表明，BSFO算法对于大部分测试函数的结果较为理想。将BSFO算法用于材料试验机电液位置伺服系统的PID控制器参数寻优仿真，获得了较好的控制性能。

关键词: 细菌群觅食优化算法, 粒子群优化算法, 细菌觅食算法, PID控制器, 电液位置伺服系统

CLC Number:

TP13
TP18

Chen Dongning, Zhang Guofeng, Yao Chengyu, Zhang Ruixing, . Bacterial Swarm Foraging Optimization Algorithm and Its Application in Optimization of PID Parameters[J]. China Mechanical Engineering, 2014, 25(1): 59-64.

陈东宁, 张国峰, 姚成玉, 张瑞星, . 细菌群觅食优化算法及PID参数优化应用[J]. 中国机械工程, 2014, 25(1): 59-64.

References

[1]Zhao J H，Liu Z H，Dao M T. Reliability Optimization Using Multiobjective Ant Colony System Approaches[J]. Reliability Engineering and System Safety，2007，92(1)：109-120.
[2]仇国庆，唐贤伦，庄陵，等．基于混沌粒子群优化的神经网络在旋转机械故障诊断中的应用[J]．中国机械工程，2008，19(21)：2642-2645.
Qiu Guoqing，Tang Xianlun，Zhuang Ling，et al. Application of Neural Network Trained by Chaos Particle Swarm Optimization to Fault Diagnosis for Rotating Machinery[J]. China Mechanical Engineering，2008，19(21)：2642-2645.
[3]魏峰涛，宋俐，李言，等．基于改进粒子群算法的四辊轧机机座结构优化设计[J]．中国机械工程，2012，23(19)：2361-2365.
Wei Fengtao，Song Li，Li Yan，et al. Optimal Structural Design of 4-roller Rolling Mill Frame Based on an IPSO Algorithm[J]. China Mechanical Engineering，2012，23(19)：2361-2365.
[4]Passino K M. Biomimicry of Bacterial Foraging for Distributed Optimization and Control[J]. IEEE Control Systems Magazine，2002，22(3)：52-67.
[5]易军，李太福．求解作业车间调度的变邻域细菌觅食优化算法[J]．机械工程学报，2012，48(12)：178-183.
Yi Jun，Li Taifu. Bacterial Foraging Optimization Algorithm Based on Variable Neighborhood for Job-shop Scheduling Problem[J]. Chinese Journal of Mechanical Engineering，2012，48(12)：178-183.
[6]高政威，庞哈利，汪定伟．基于菌群自适应觅食的公交调度建模仿真与优化[J]．系统仿真学报，2011，23(6)：1151-1155，1160.
Gao Zhengwei，Pang Hali，Wang Dingwei. Adaptive Bacterial Foraging Optimization and Its Application for Bus Scheduling[J]. Journal of System Simulation，2011，23(6)：1151-1155, 1160.
[7]Biswas A，Desgupta S，Das S，et al. Synergy of PSO and Bacterial Foraging Optimization - A Comparative Study on Numerical Benchmarks[J]. Innovations in Hybrid Intelligent Systems，Advances in Soft Computing.， 2007，44：255-263.
[8]陈东宁，姜万录，王益群．基于粒子群算法的冷连轧机轧制负荷分配优化[J]．中国机械工程，2007，18(11)：1303-1306.
Chen Dongning，Jiang Wanlu，Wang Yiqun. Load Distribution Optimization of Tandem Cold Mill Based on PSO Algorithm[J]. China Mechanical Engineering， 2007，18(11)：1303-1306.
[9]Shi Y，Eberhart R. A Modified Particle Swarm Optimizer[C]//IEEE International Conference on Evolutionary Computation. Anchorage，1998：69-73.
[10]Huang T，Mohan A S. Micro-particle Swarm Optimizer for Solving High Dimensional Optimization Problems(μPSO for High Dimensional Optimization Problems)[J]. Applied Mathematics and Computation，2006，181(2)：1148-1154.

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Bacterial Swarm Foraging Optimization Algorithm and Its Application in Optimization of PID Parameters

细菌群觅食优化算法及PID参数优化应用

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