ANFIS: Self-tuning Fuzzy PD Controller for Twin Rotor MIMO System

被引:7
作者
Mahmoud, Thair S. [1 ]
Marhaban, Mohammad H. [1 ]
Hong, Tang S. [1 ]
机构
[1] Univ Putra Malaysia, Dept Elect & Elect Engn, Upm Serdang 43400, Selangor, Malaysia
关键词
twin rotor MIMO system; self-tuning fuzzy PD controller; ANFIS fuzzy subtractive clustering method;
D O I
10.1002/tee.20543
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This work presents a self-tuning fuzzy PD controller for solving the control challenges of twin rotor MIMO system The controller is made adaptive through output scaling factor adjustment of the updating factor. alpha The value of alpha is calculated directly from a fuzzy rule base defined as error and change of error of the controlled variable A combination of adaptive neural fuzzy inference system and fuzzy subtractive clustering method was used, where the objective was to improve its time response. while reducing its computational complexity Simulation results show performance improvement in comparison with that of the previous method (C) 2010 Institute of Electrical Engineers of Japan Published by John Wiley & Sons. Inc
引用
收藏
页码:369 / 371
页数:3
相关论文
共 10 条
[1]   Hybrid control scheme for tracking performance of a flexible system [J].
Aldebrez, F. M. ;
Alam, M. S. ;
Tokhi, M. O. .
CLIMBING AND WALKING ROBOTS, 2006, :543-550
[2]  
Chiu S, 1996, 1996 BIENNIAL CONFERENCE OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY - NAFIPS, P461, DOI 10.1109/NAFIPS.1996.534778
[3]  
CHOPRA S, 2007, INT J INTELLIGENT TE, V2, P78
[4]  
Juang JG, 2005, 2005 IEEE International Conference on Mechatronics, P102
[5]  
JUANG JG, 2006, INT C NEUR INF PROC, P654
[6]   Optimal fuzzy switching grey prediction with RGA for TRMS control [J].
Juang, Jih-Gau ;
Tu, Kai-Ti ;
Liu, Wen-Kai .
2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGS, 2006, :681-+
[7]  
RAHIDEH A, 2006, 32 ANN C IEEE IND EL, P48
[8]  
Shih CL, 2008, ASIAN J CONTROL, V10, P107, DOI 10.1002/asjc.011
[9]  
Wang H, 2006, 2006 3RD INTERNATIONAL IEEE CONFERENCE INTELLIGENT SYSTEMS, VOLS 1 AND 2, P9
[10]  
*WIND SYS, 18 WIND SYS