APPLICATION FEATURES OF FUZZY CONTROLLERS ON EXAMPLE OF DC MOTOR SPEED CONTROL
Read the full article
For citation: Demidova G.L., Kuzin А.Yu., Lukichev D.V. Application features of fuzzy controllers on example of DC motor speed control. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2016, vol. 16, no. 5, pp. 872–878. doi: 10.17586/2226-1494-2016-16-5-872-878
A prerequisite for the use of intelligent control methods, including algorithms of fuzzy logic, is increasing complexity in all industries, especially when parameters of technical systems while in operation vary in wide range. The paper provides comparative analysis of the basic types of common fuzzy direct action controllers on the example of speed control system in the DC motor drive. Design features of these types of fuzzy controllers are shown. Their comparison with traditional PI controller is carried out through the use of simulation, including the conditions of uncertainty expressed in changing of equivalent moment of inertia of the motor shaft. As a result, the conclusion about the feasibility of fuzzy PID-type controller application is made. The features of fuzzy controllers outlined in the paper can be summarized to more complex motor drive systems and to other non-linear systems that require the maintenance of any parameter within a given range.
Acknowledgements. The work is partially financially supported by the Government of the Russian Federation (grant 074-U01).
1. Ang K.H., Chong G., Li Y. PID control system analysis, design, and technology. IEEE Transactions on Control Systems Technology, 2005, vol. 13, no. 4, pp. 559–576. doi: 10.1109/TCST.2005.847331
2. Quevedo J., Escobet T. Digital control: past, present and future of PID control. Proc. IFAC Workshop. Terrassa, Spain, 2000.
3. Ziegler J.G., Nichols N.B. Optimum settings for automatic controllers. Trans. ASME, 1942, vol. 64, pp. 759–768.
4. Demidova G.L., Lovlin S.Yu., Tsvetkova M.Kh. Synthesis of follow-up electric drive of telescope’s azimuth axis with reference model in position contour. Vestnik ISPU, 2011, no. 2, pp. 77–81. (In Russian)
5. Metody Robastnogo, Neiro-Nechetkogo i Adaptivnogo Upravleniya [Methods of Robust, Neuro-Fuzzy and Adaptive Control]. Ed. N.D. Egupov. 2nd ed. Moscow, MGTU Publ., 2002, 744 p.
6. Gostev V.I. Fuzzy Controllers in Automatic Control Systems. Kiev, Radioamator Publ., 2008, 972 p. (In Russian)
7. Sheng O., Haishan L., Guoying L., Guohui Z., Xing Z., Qingzhen W. A fuzzy PI speed controller based on feedback compensation strategy for PMSM. International Journal of Advanced Computer Science and Applications, 2015, vol. 6, no. 5, pp. 49–54.
8. Amosov O.S., Amosova L.N., Ivanov S.N. The synthesis of the optimum control systems for electromechanical heat generating complexes with using fuzzy systems. Information Science and Control Systems, 2009, no. 1, pp. 73–83. (In Russian)
9. Khizhnyakov Yu.N., Yuzhakov A.A. Neuro-fuzzy voltage controller for the object of management. Journal of Instrument Engineering, 2011, vol. 554, no. 12, pp. 51–56.
10. Usol'tsev A.A., Smirnov N.A. Fuzzy controller in servo drive control system with speed limitation. Vestnik ISPU, 2011, no. 3, pp. 27–32.
11. Lukichev D.V., Demidova G.L. Fuzzy control system of positioning servo drives of elastic coupling rotary supports. Vestnik ISPU, 2013, no. 6, pp. 60–64.
12. Kupriyanchik D.V., Denisov K.M., Lukichev D.V., Zhdanov I.N. Hardware implementation of fuzzy logic in the structure of the educational laboratory complex. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2006, no. 33, pp. 169–173. (In Russian)
13. Derugo P., Szabat K. Implementation of the low computational cost fuzzy PID controller for two-mass drive system. Proc. 16th Int. Power Electronics and Motion Control Conference and Exposition, PEMC. Antalya, Turkey, 2014, pp. 564–568. doi: 10.1109/EPEPEMC.2014.6980554
14. Kaminski M., Szabat K. Neuro-fuzzy state space controller for drive with elastic joint. Proc. 11th IEEE Int. Conf. on Power Electronics and Drive Systems. Sydney, Australia, 2015, pp. 373–378. doi: 10.1109/PEDS.2015.7203559
15. Lukichev D.V., Demidova G.L, Brock S. Fuzzy adaptive PID control for two-mass servo-drive system with elasticity and friction. Proc. 2nd IEEE Int. Conf. on Cybernetics, CYBCONF. Gdynia, Poland, 2015, pp. 443–448. doi: 10.1109/CYBConf.2015.7175975
16. Klyuchev V.I. Electric Drive Theory: Textbook. 2nd ed. Moscow, Energoatomizdat Publ., 2001, 704 p. (In Russian)
17. Uskov A.A. Sistemy s Nechetkimi Modelyami Ob"ektov Upravleniya [Systems with Fuzzy Models of Controlled Objects]. Smolensk, 2013, 153 p.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License