Machine Vision-based for Development a Sun Tracking using Intelligent Algorithm

Riza Muhida

Abstract


In this project, Two degree of freedom (DOF) of light tracking system using fuzzy logic control is presented in this paper. The fuzzy control for light tracking system (FLTS) uses a web-camera as a vision sensor, two PC sound cards as output signal controller, and two DC motors as a pan-tilt driver mechanism. The Fuzzy logic controller to control the camera panel angles of light tracking system is designed. Two fuzzy controllers are proposed, one for each motor to produce proper PWM in order to track the light source. A typical FLC includes three basic components, an input signal fuzzification, a fuzzy engine, and an output signal defuzzification. The Fuzzy controller input parameters (Xcp,Ycp) and variation of duty cycle output parameters are used  to generate  the optimal pulse-width- modulated (PWM) to track the light source, such that PWM is generated under different operating conditions to drive the motors. The motors will react accordingly when they receive signal from the sound card to make sure the camera always focuses on the centroid of the light source. The system tested at different locations. The data which were obtained by experiment were able to show a validity of the proposed controller.

Keywords


DC Motor, Duty Cycle; Fuzzification; Image Processing; PWM; Sound Card; Vision Sensor; Webcamera

Full Text:

PDF

References


Soteris Kalogirou, Kostas Metaxiotis, Adel Mellit, Artifcial Intelligence Techniques for Modern Energy Applications. IGI Global, 2010.

Muhammad Faheem Khan, Rana Liaqat Ali. (2009, Nov.) seminarprojects.[Online]. VIEW

U. Yolac, T. Yalcinoz, "Comparison of fuzzy logic and PID controllers for TCSC using Matlab," in Universities Power Engineering Conference, Turkey, 2004, pp. 438-442.

C.Y. Won, D.H. Kim, S.C. Kim, W.S. Kim, H.S. Kim, "A New Maximum Power Point Tracker of Photovoltaic Arrays using Fuzzy Controller," in Proceedings of the IEEE Power Elec. Specialists Conference, 1994, pp. 396-403.

Li, Y.F. Lau, C.C., "Development of fuzzy algorithms for servo systems," Control Systems Magazine, IEEE, vol. 9, no. 3, pp. 65-72, Apr. 1989. CrossRef

K. M. Passino and S. Yurkovich, Fuzzy Control. Addison-Wesley-Longman, Menlo Park, CA, 1998.

Jung-Sik Choi Do-Yeon Kim Ki-Tae Park Chung-Hoon Choi Dong-Hwa Chung, "Design of Fuzzy Controller based on PC for Solar Tracking System," in International Conference on Smart Manufacturing Application, KINTEX, Gyeonggi-do, Korea, 2008, pp. 508-513.

Dr. Odry Peter, Diveki Szabolcs, Csasznyi Andor, Burany Nandor, "Fuzzy Logic Motor Control with MSP430x14x," Instruments Incorporated, Texas, Application Report SLAA235, 2005.

Ying-Shieh Kung Chang-Ming Liaw, "A fuzzy controller improving a linear model following controller for motor drives," Fuzzy Systems, IEEE Transactions on, vol. 2, no. 3, pp. 194-202, Aug. 1994. CrossRef

W. Pedrycz, "Fuzzy Control and Fuzzy Sysfems," Research Studies Press (RSP) Itd 0471 9231 17, 1989.


Refbacks

  • There are currently no refbacks.




Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.