Volume 1, Number 2 (2016)
Year Launched: 2016
Journal Menu
Previous Issues
Why Us
-  Open Access
-  Peer-reviewed
-  Rapid publication
-  Lifetime hosting
-  Free indexing service
-  Free promotion service
-  More citations
-  Search engine friendly
Contact Us
Email:   service@scirea.org
Home > Journals > SCIREA Journal of Electrics, Communication > Archive > Paper Information

Trajectory Control of a Variable Loaded Servo System by using Fuzzy Iterative Learning PID Control

Volume 1, Issue 2, December 2016    |    PP. 85-98    |PDF (691 K)|    Pub. Date: December 27, 2016
174 Downloads     1963 Views  

Omer Aydogdu, Department of Electrical and Electronics Engineering, Selcuk University, Alaeddin Keykubat Campus, 42075, Selcuklu, Konya,Turkey.
Mehmet Latif Levent, Department of Electrical and Electronics Engineering, Selcuk University, Alaeddin Keykubat Campus, 42075, Selcuklu, Konya,Turkey.

In this study, trajectory control of the Variable Loaded Servo (VLS) system is performed by using a Fuzzy Logic based Iterative Learning Control (ILC) method. In the study, a Iterative Learning PID (IL-PID) Controller is used as the iterative learning control structure. Also, a fuzzy adjustment mechanism has been added to the control system for specify the initial parameter of the IL-PID controller. So, with combining the fuzzy logic based parameter adjustment mechanism and the IL-PID controller, Fuzzy Iterative Learning PID (Fuzzy IL-PID) controller is designed to improving the system performance. In the designed system, thanks to the fuzzy adjustment mechanism, the IL-PID controller parameters such as Kp, Ki, and Kd values are automatically adjusted to the appropriate values initially. To illustrate the effectiveness of the proposed fuzzy IL-PID controller, trajectory control of the variable loaded servo system was performed by using both Fuzzy PID and Fuzzy IL-PID control methods under the same conditions separately, and the obtained results were compared. It is seen from the results, the proposed Fuzzy IL-PID control method is to better compensate the system effect as time varying loads and has reduced the steady-state error more than other method in iterations progresses.

Fuzzy PID control, Fuzzy IL-PID control, Trajectory control, Variable loaded servo system

Cite this paper
Omer Aydogdu, Mehmet Latif Levent, Trajectory Control of a Variable Loaded Servo System by using Fuzzy Iterative Learning PID Control, SCIREA Journal of Electrics, Communication. Vol. 1 , No. 2 , 2016 , pp. 85 - 98 .


[ 1 ] Baek, S. M., Kuc, T. Y. “An adaptif PID learning Control of DC motors,” IEEE International Conference on Computational Cybernetics and Simulation, Orlando, FL, 1997, vol. 3, pp. 2877-2882. DOI: 10.1109/ICSMC.1997.635431
[ 2 ] Zadeh, L. A. “Outline of a new approach to the analysis of complex systems and decision processes.” IEEE trans. on systems, Man and Cybernatics, vol. 3, no. 1, pp.28-44, 1973.
[ 3 ] Elshazly, O., El-Bardini, M. “Development of self-tuning fuzzy iterative learning control for controlling a mechatronic system.” International Journal of Information and Electronics Engineering, vol. 2, no. 4, pp. 565-569, July, 2012. DOI: 10.7763/IJIEE.2012.V2.162
[ 4 ] Pok, Y. M. Liew, K. H. and Xu, J. X. “Fuzzy PD iterative learning control algorithm for improving tracking accuracy,” IEEE International Conference on Systems, Man and Cybernatics, San Diego, CA, 1998, vol. 2, pp. 1603-1608. DOI: 10.1109/ICSMC.1998.728117.
[ 5 ] Wei, J. “Adaptive iterative learning control for a class of nonlinear time-varying systems with unknown delays and input dead-zone.” IEEE/CAA Journal of Automatica Sinica, vol. 1, no. 3, pp. 302-314, July, 2014. DOI: 10.1109/JAS.2014.7004688.
[ 6 ] Hu, C. R., Lin, S. S. Sheng, H. Z. “A new discrete-time adaptive ILC for nonlinear systems with time-varying parametric uncertainties.” Acta Automatica Sinica, vol. 34, no. 7, pp. 805-808. 2008 (in Chinese). DOI: 10.3724/SP.J.1004.2008.00805.
[ 7 ] Alkan, O., Aydogdu, O. “Fuzzy model reference learning control of a time-varying rotary servo systems,” Proceedings of Second International Conference on Informatics, Çanakkale, (ICI'2011), 2011, pp. 1-7.
[ 8 ] Kasnakoglu, C., “Modeling and control of flow problems by adaptation-based linear parameter varying models.” Turkish Journal of Electrical Engineering & Computer Sciences, vol. 18, 2010. DOI:10.3906/elk-0906-5.
[ 9 ] Fadil, M.A., “PID Controller for Micro-Unmanned Air Vehicle (Micro-UAV).” BS thesis, Mekanikal-Aeronautik, Universiti Teknologi, Kuala Lumpur, Malaysia, 2012.
[ 10 ] Precup, R. E., Preitl, S., Petriu, E. M., Tar, J. K. and Fodor, J. “Iterative learning-based fuzzy control system,” in IEEE International Workshop on Robotic and Sensors Environments, Ottawa, Canada, 2008, pp. 25-28.
[ 11 ] Dotoli, M., Maione, B. and Turchiano, B. “Fuzzy-Supervised PID Control: Experimental Results,” in 1st European Symposium on Intelligent Technologies, Tenerife, Spain, EUNITE 2001, pp. 31–35.
[ 12 ] Feng, G. “A Survey on Analysis and Design of Model-Based Fuzzy Control Systems.” IEEE Trans. on Fuzzy Sys., vol. 14, no. 5, pp. 676–697, October, 2006. DOI: 10.1109/TFUZZ.2006.883415
[ 13 ] Lee, C. C. “Fuzzy Logic in Control Systems: Fuzzy Logic Controller-Part I.” IEEE Transactions on Systems, Man and Cybernetics, vol. 20, no. 2, pp. 404–418, March/April, 1990.
[ 14 ] Ahn, H. S., Chen, Y. Q. and Moore, K. L. “Iterative Learning Control: Brief Survey and Categorization.” IEEE Transactions On Systems, Man, And Cybernetics, Part C: Applications And Reviews, vol. 37, no. 6, pp 1099-1121, November, 2007. DOI: 10.1109/TSMCC.2007.905759
[ 15 ] Arimoto, S., Kawamura, S., and Miyazaki, F. “Bettering operation of dynamic systems by learning: A new control theory for servomechanism and mechatronics systems,” The 23rd IEEE Conference on Decision and Control, Las Vegas, NV, 1984, pp. 1064-1063. DOI: 10.1109/CDC.1984.272176
[ 16 ] Fadil, M. A., Jalil N. A., and Mat Darus, I. Z. “Intelligent PID controller using iterative learning algorithm for active vibration controller of flexible beam,” IEEE Symposium on Computers & Informatics, Langkawi, ISCI, 2013, pp. 80-85. DOI: 10.1109/ISCI.2013.6612380.

Submit A Manuscript
Review Manuscripts
Join As An Editorial Member
Most Views
by Sergey M. Afonin
2935 Downloads 43486 Views
by Syed Adil Hussain, Taha Hasan Associate Professor
2295 Downloads 19985 Views
by Omprakash Sikhwal, Yashwant Vyas
2366 Downloads 16687 Views
by Munmun Nath, Bijan Nath, Santanu Roy
2263 Downloads 16608 Views
Upcoming Conferences