Title
Artificial Intelligence - I: Fuzzy logic based robust pole-placement controller for DC-DC buck converter
Abstract/Description
This paper describes the fuzzy logic based robust pole-placement controller for the buck converter working in Continuous Conduction Mode (CCM). The converter operates at a switching frequency of 500 KHz. Pole-placement controller does not show good robustness to the load variations and the change in supply and reference voltages. In order to improve the static and dynamic properties, pole-placement controller supported by decomposed PID fuzzy algorithm is investigated. The performance of both the controllers, pole-placement and optimal pole-placement, is compared and conclusions are drawn. It will be shown that optimal control shows better dynamic performance. MATLAB/SIMULINK based simulation results validate the design.
Location
Room C5
Session Theme
Artificial Intelligence – I
Session Type
Other
Session Chair
Dr. Sajjad Haider
Start Date
23-7-2011 3:55 PM
End Date
23-7-2011 4:15 PM
Recommended Citation
Abbas, G., Farooq, U., & Asad, M. U. (2011). Artificial Intelligence - I: Fuzzy logic based robust pole-placement controller for DC-DC buck converter. International Conference on Information and Communication Technologies. Retrieved from https://ir.iba.edu.pk/icict/2011/2011/17
COinS
Artificial Intelligence - I: Fuzzy logic based robust pole-placement controller for DC-DC buck converter
Room C5
This paper describes the fuzzy logic based robust pole-placement controller for the buck converter working in Continuous Conduction Mode (CCM). The converter operates at a switching frequency of 500 KHz. Pole-placement controller does not show good robustness to the load variations and the change in supply and reference voltages. In order to improve the static and dynamic properties, pole-placement controller supported by decomposed PID fuzzy algorithm is investigated. The performance of both the controllers, pole-placement and optimal pole-placement, is compared and conclusions are drawn. It will be shown that optimal control shows better dynamic performance. MATLAB/SIMULINK based simulation results validate the design.
