全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
-  2016 

双闭环Buck变换器系统模糊PID控制
A Fuzzy PID Control Strategy for Buck Converter System of Double Closed Loop Circuits

DOI: 10.7652/xjtuxb201604006

Keywords: Buck变换器,双闭环,模糊PID控制,参数自整定
buck converter
,double loop circuit,fuzzy PID control,parameters self??tuning

Full-Text   Cite this paper   Add to My Lib

Abstract:

针对传统线性PID控制对复杂控制对象难以建模及人工整定经验缺乏等问题,提出了一种双闭环Buck变换器系统的模糊PID控制策略。首先,设计了电压外环和电流内环结构以同时提高系统的抗扰性和跟随性;其次选择高斯函数和三角形函数相结合的隶属度函数以使控制器对小误差的灵敏度得以增强;接着,针对PID参数分别设计了3个子推理器并通过基于专家经验的规则库制定出Buck变换器的模糊规则,可以使控制器不依赖于Buck变换器系统精确的数学模型,从而克服传统PID控制导致的输出电压高超调、振荡等缺点;最后,设计了一套新型双闭环Buck变换器硬件系统,利用STM32单片机将模糊PID算法首次用于控制变化速度快、时滞小的被控量。实验结果表明:模糊PID控制策略不仅能够提高输出电压跟踪精度,还能有效抑制负载扰动及参数摄动,在阶跃启动下,系统输出电压超调量低于10%,调节时间低于3 ms;与传统PID单环系统相比,其输出电压纹波、扰动下的最大动态压降和恢复时间均减小了一个数量级以上。
A novel fuzzy PID control strategy of Buck converter system with double closed loop structures is proposed to solve problems that complex control objects are difficult of modeling and the artificial tuning experiences are lack, etc. The voltage and current loop structures are designed to improve both the anti??disturbance performance and the following performance of the system. A membership function that combines the Gauss function and the triangular function is selected to enhance the sensitivity of the controller to small error. Three sub inference devices are designed based on the PID parameters and the rule base of expert experiences, and the fuzzy rule of Buck converter is developed to make the designed controller independent of the precise mathematical model of Buck converter. So that it overcomes the high percent overshoot, oscillation and other shortcomings of the output voltage caused by traditional PID controls. A new Buck converter system of double closed loop circuits is designed, and the fuzzy PID control strategy is applied to control the quantities with rapid change and small time delay by making use of STM32. Experimental results show that the fuzzy PID control strategy not only improves the tracking accuracy of the output voltage, but also effectively suppresses the load disturbance and parameter perturbation, and that the overshoot of the output voltage is less than 10% and the adjustment time is less than 3 ms under the step to start. A comparison with the traditional PID system show that the designed system’s output voltage ripple, maximum dynamic voltage drop and recovery time under the disturbance are reduced by one order of magnitude

References

[1]  [5]丁芳, 贾翔宇, 李科伟, 等. 模糊算法在智能车控制中的应用 [J]. 中国民航大学学报, 2009, 27(1): 27??30.
[2]  [13]封琦. 基于模糊控制的Boost有源功率因数校正器设计与研究 [D]. 南京: 河海大学, 2006.
[3]  [6]LI Jun, LIU Junhua. Nonlinear inverse modeling of sensor based on back??propagation fuzzy logical system [J]. Academic Journal of Xian Jiaotong University, 2007(1): 14??17.
[4]  [7]李胜男, 张浩, 马西奎, 等. Buck??Boost DC/DC变换器中边界碰撞分岔现象的实验研究 [J]. 西安交通大学学报, 2006, 40(4): 454??458.
[5]  NI Jun??Kang, LIU Chong??Xin, PANG Xia. Fuzzy fast terminal sliding mode controller using an equivalent control for chaotic oscillation in power system [J]. Acta Physica Sinica, 2013, 62(19): 190507.
[6]  [11]KARASAKAL O, GUZELKAYA M, EKSIN I, et al. Online tuning of fuzzy PID controllers via rule weighing based on normalized acceleration [J]. Engineering Applications of Artificial Intelligence, 2013, 26(1): 184??197.
[7]  [14]倪骏康, 刘崇新, 庞霞. 电力系统混沌振荡的等效快速终端模糊滑模控制 [J]. 物理学报, 2013, 62(19): 190507.
[8]  WEN Le, GAO Lin, DAI Yiping. Study on fuzzy PID control of turbine??driven centrifugal compressor [J]. Journal of Xi’an Jiaotong University, 2011, 45(7): 76??81.
[9]  [1]施三保, 夏泽中. DC??DC变换器的模糊自适应PID控制仿真研究 [J]. 武汉理工大学学报: 信息与管理工程版, 2006, 28(8): 20??23.
[10]  SHI Sanbao, XIA Zezhong. Simulation study of fuzzy adaptive PID control of DC??DC converters [J]. Journal of Wuhan University of Technology: Information and Management Engineering, 2006, 28(8): 20??23.
[11]  [2]李竞, 胡保生. 模糊PID增益调节器的算法、结构及硬件实现 [J]. 西安交通大学学报, 1998, 32(5): 9??13.
[12]  LI Jing, HU Baosheng. Algorithm, architecture and FPGA implementation for fuzzy PID gain conditioner [J]. Journal of Xi’an Jiaotong University, 1998, 32(5): 9??13.
[13]  [3]陈岩, 杜晓明. 模糊PID控制在温室环境中的应用 [J]. 农机化研究, 2010, 32(8): 173??177.
[14]  CHEN Yan, DU Xiaoming. Application fuzzy PID control in the greenhouse environment [J]. Agricultural Mechanization Research, 2010, 32(8): 173??177.
[15]  [4]李岩. 模糊PID控制在液位控制中的应用 [D]. 合肥: 合肥工业大学, 2008.
[16]  LI Yan. The application on fuzzy PID control in water level control system [D]. Hefei: Hefei University of Technology, 2008.
[17]  DING Fang, JIA Xiangyu, LI Kewei, et al. Application of fuzzy algorithm in smart car [J]. Journal of Civil Aviation University of China, 2009, 27(1): 27??30.
[18]  LI Shengnan, ZHANG Hao, MA Xikui, et al. Experimental study of border collision bifurcation in buck??boost DC/DC power converters [J]. Journal of Xi’an Jiaotong University, 2006, 40(4): 454??458.
[19]  [8]文乐, 高林, 戴义平. 透平压缩机组的模糊PID控制与特性研究 [J]. 西安交通大学学报, 2011, 45(7): 76??81.
[20]  [9]ZADEH L A. Fuzzy sets [J]. Information and Control, 1965, 65(8): 338??353.
[21]  [10]罗光明, 黄晓宇, 朱建林. 基于MATLAB的模糊自整定PID参数控制器计算机仿真 [J]. 机械与电子, 2001(2): 23??26.
[22]  LUO Guangming, HUANG Xiaoyu, ZHU Jianlin. Computer simulation of fuzzy self??tuning PID control based on MATLAB [J]. Machinery and Electronics, 2001(2): 23??26.
[23]  [12]WAEWSAK Y C, NOPHARATANA A, CHAIPRASERT P, et al. Neural??fuzzy control system application for monitoring process response and control of anaerobic hybrid reactor in wastewater treatment and biogas production [J]. Journal of Environmental Sciences, 2010, 22(12): 1883??1890.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133