Design and Simulation of a PID Controller Based on Fuzzy Control

被引:0
作者
Wu, Chenbin [1 ]
Li, Haiming [1 ]
Wu, Lei [1 ]
机构
[1] Shanghai Univ Elect Power, Sch Comp & Informat Engn, Shanghai, Peoples R China
来源
PROCEEDINGS OF THE 2014 INTERNATIONAL CONFERENCE ON MECHATRONICS, CONTROL AND ELECTRONIC ENGINEERING | 2014年 / 113卷
关键词
Fuzzy control; PID control; Simulation modeling; Delay lag link; Fuzzy PID Controller;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
According to the fuzzy control theory, the paper describes the principle and feature of the fuzzy control by fuzzy control having strong robustness in allusion to the control system which has the characteristics of pure hysteresis and unprecise parameter time-variance and model. On this basis, it conducts the design and algorithm of the fuzzy controller. And it emulates the related project content by the use of Simulink software package of MATLAB in order to test and verify the availability of the project. Besides, in this paper, in order to deal with the delay lag link, deviation and deviation change rate are taken as inputs, a fuzzy inference method is utilized to optimize the traditional PID control, and the controller is designed and simulated with MATLAB. Good control performance can be acquired from the simulation result, the fuzzy PID controller improves the dynamic and static performance of the system. Combining the fuzzy control and PID control together can get their good qualities, which also has good practical significance and research value.
引用
收藏
页码:767 / 770
页数:4
相关论文
共 19 条
[1]  
Aiping Shi, 2011, 2011 International Conference on Electrical and Control Engineering, P1354, DOI 10.1109/ICECENG.2011.6057256
[2]   FUZZY MAPPING AND CONTROL [J].
CHANG, SSL ;
ZADEH, LA .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1972, SMC2 (01) :30-&
[3]  
Cui GM, 2012, PROCEEDINGS OF THE 10TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA 2012), P1553, DOI 10.1109/WCICA.2012.6358125
[4]  
Huang Y, 2000, NINTH IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE 2000), VOLS 1 AND 2, P969, DOI 10.1109/FUZZY.2000.839169
[5]  
Keliang Zhou, 2011, 2011 Second International Conference on Mechanic Automation and Control Engineering, P7200
[6]   A neural fuzzy system with fuzzy supervised learning [J].
Lin, CT ;
Lu, YC .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 1996, 26 (05) :744-763
[7]  
Ma FY, 2014, CHIN CONT DECIS CONF, P3840, DOI 10.1109/CCDC.2014.6852849
[8]   Fuzzy self-organization, inferencing, and rule generation [J].
Mitra, S ;
Pal, SK .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, 1996, 26 (05) :608-620
[9]   A RECONFIGURABLE FUZZY NEURAL-NETWORK WITH IN-SITU LEARNING [J].
PEDRYCZ, W ;
POSKAR, CH ;
CZEZOWSKI, PJ .
IEEE MICRO, 1995, 15 (04) :19-30
[10]  
Petrov M, 2002, 2002 FIRST INTERNATIONAL IEEE SYMPOSIUM INTELLIGENT SYSTEMS, VOL 1, PROCEEDINGS, P30, DOI 10.1109/IS.2002.1044224