Omer Aydogdu, Mehmet Latif Levent



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

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In this study, trajectory control of the variable loaded servo system is performed by using a Fuzzy Logic based Iterative Learning Control (ILC) method. As the iterative learning control structure, a Iterative Learning PID (IL-PID) Controller is used in the study. 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 based parameter adjustment mechanism and the IL-PID controller, Fuzzy Iterative Learning PID (Fuzzy ILPID) 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 experimental 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


[1] S. M. Baek, T. Y. Kuc, An adaptif PID learning Control of DC motors, IEEE International Conference on Computational Cybernetics and Simulation, Orlando, FL, 1997, vol. 3, pp. 2877-2882.

[2] L. A. Zadeh, 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] O. Elshazly, M. El-Bardini, 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.

[4] Y. M. Pok, K. H. Liew, and J. X. Xu, 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.

[5] J. Wei, 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.

[6] C. R. Hu, S. S. Lin, H. Z. Sheng, 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).

[7] O. Alkan, O. Aydogdu, 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] C. Kasnakoglu, Modeling and control of flow problems by adaptation-based linear parameter varying models, Turkish Journal of Electrical Engineering & Computer Sciences, vol. 18, 2010.

[9] M.A. Fadil, PID Controller for Micro- Unmanned Air Vehicle (Micro-UAV), BS thesis, Mekanikal-Aeronautik, Universiti Teknologi, Kuala Lumpur, Malaysia, 2012.

[10] R. E. Precup, S. Preitl, E. M. Petriu, J. K. Tar, and J. Fodor, Iterative learning-based fuzzy control system, in IEEE International Workshop on Robotic and Sensors Environments, Ottawa, Canada, 2008, pp. 25- 28.

[11] M. Dotoli, B. Maione and B. Turchiano, Fuzzy-Supervised PID Control: Experimental Results, in 1st European Symposium on Intelligent Technologies, Tenerife, Spain, EUNITE 2001, pp. 31–35.

[12] G. Feng, 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.

[13] C. C. Lee, 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] H. S. Ahn, Y. Q. Chen and K. L. Moore, 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.

[15] S. Arimoto, S. Kawamura, F. Miyazaki, Bettering operation of dynamic systems by learning: A new control theory for servomechanisin and mechatronics systems, The 23rd IEEE Conference on Decision and Control, Las Vegas, NV, 1984, pp. 1064-1063.

[16] M. A. Fadil, N. A. Jalil and I. Z. Mat Darus, 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.

Cite this paper

Omer Aydogdu, Mehmet Latif Levent. (2017) Trajectory Control of a Variable Loaded Servo System by using Fuzzy Iterative Learning PID Control. International Journal of Control Systems and Robotics, 2, 170-177


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