HARDWARE DESIGN AND IMPLEMENTATION OF GENETIC ALGORITHM FOR THE CONTROLLER OF A DC TO DC BOOST CONVERTER
DOI:
https://doi.org/10.11113/jt.v78.8725Keywords:
Genetic Algorithm, Booster PIDAbstract
Controllers for DC to DC Boost Converters have evolved from simple control method to those that involve the use of fuzzy logic controllers.  In many implementations, Proportional Integral Derivative (PID) controllers are commonly employed. In this paper, a genetic algorithm for tuning the PID controller of a DC to DC Boost Converter is hardware modelled and implemented on a Field Programmable Gate Array (FPGA) using Verilog as tool for the design entry. The goal of embedding genetic algorithm into the controller is to search for the best PID parameters that will yield fast settling time of the booster at an output of 6V. The hardware implementation allows the controller to tune itself by searching for the best Kp, Ki and Kd values that will give the best settling time. Significantly, this eliminates the need for a separate computer to do the searching routine.  Test results of the circuit implemented yielded promising results.  When compared to previous researches, the genetic algorithm employed yielded good PID parameters that resulted to a settling time as low as less than 60msec.
References
Yeong-Tsair Lin, Wen-Yaw Chung. 2005. A Monolithic CMOS Step-Down DC-DC Converter, Circuits and Systems, 2005. 48th Midwest Symposium on, Aug 2005
Wan-Rone Liou et al. 2007. A High Efficiency Dual-Mode Buck Converter IC For Portable Applications Communications, Circuits and Systems, 2007. ICCCAS 2007. International Conference on, July 2007
Islam ,M. Murshidul, Allee , David R., Konasani , Siva, and Rodriguez, Armando A. Rodriguez, 2004. A Low-Cost Digital Controller for a Switching DC Converter with Improved Voltage Regulation, IEEE Power Electronics Letters, 2(4): 121-124.
Dumalag, Lawrence and Yap, Roderick. 2012 FPGA Based Multi-Decision Level PID Controller for Boost Converter, 5th AUN/SEEDNET Regional Conference on Information and Communications Technology.
K.Sundareswaran et. al. 2010. Robust Controller Identification for a Boost Type DC-DC Converter Using Genetic Algorithm. 2008 IEEE Region 10 Colloquium and the Third ICIIS, Kharagpur.
Pengfei Guo et al. 2010. The Enhanced Genetic Algorithms for the Optimization Design, 2010 3rd International Conference on Biomedical Engineering and Informatics (BMEI 2010).
Tai-Shan Yan et. al. 2007. Research on Handwritten Numerical Recognition Method Based On Improved Genetic Algorithm AND Neural Network, Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, Beijing, China.
Hongze Qiu et. al. 2009. A Genetic Algorithm-based Approach to Flexible Job-shop Scheduling Problem. Natural Computation, 2009. ICNC '09. Fifth International Conference.
Dumalag, Lawrence. 2010. FPGA Based Multi-Decision Level PID Controller for Boost Converter, A Thesis Document, De La Salle University, Manila, Philippines, August, 2010
Dee, Robert Isaac et. al. 2010. Development of an FPGA-based controller for the implementation of a DC-DC boost converter, A Thesis Document, De La Salle University.
Caldo, R. and Yap, R. 2013. Design, development and implementation of a fuzzy logic controller for DC-DC Buck and Boost converter in an FPGA, Control, Automation and Information Sciences (ICCAIS), International Conference on, November 2013.
Pseudo-Random Number Generation Routine for the MAX765x Microprocessor [available online: https://www.maximintegrated.com/en/app-notes/index.mvp/id/1743]
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