Title: Optimal QFT controller and pre-filter for buck converter using multi-objective genetic algorithm
Authors: Nitish Katal; Shiv Narayan
Addresses: Department of Electrical Engineering, PEC University of Technology, Chandigarh, India ' Department of Electrical Engineering, PEC University of Technology, Chandigarh, India
Abstract: Buck converters are one of the most widely used convertors in applications that are dependent upon constant load voltage supply like power electronics, drive, UPS system, etc. But these convertors inherent nonlinearities because of the switching operation and continuous operation leads to the introduction of parametric uncertainties, making it difficult to assure quality output overtime. In order to mitigate such effects in this paper QFT controller has been designed. The paper explores a template and bounds free approach for the designing the QFT controller. The design problem has been posed as a multi-objective optimisation problem and solved using genetic algorithm (nsGA-II). The designed controller has been implemented for buck converter for variable input voltage and load variations. As a Pareto optimal set (POS) of solutions are obtained at the end of optimisation. The use of level diagrams has also been explored for choosing the ideal solution from POS. The results obtained have been compared with the PID controller tuned using classical method of Ziegler Nichols. As per the simulation results obtained, the designed controller offers a robust response to parametric uncertainties and also has very less current and voltage ripples; whereas the Ziegler Nichols controller fails to offer a steady output.
Keywords: quantitative feedback theory; QFT; robust stability; buck converter; level diagrams; multi-objective genetic algorithm; MOGA.
International Journal of Swarm Intelligence, 2017 Vol.3 No.2/3, pp.192 - 214
Received: 26 May 2016
Accepted: 30 Jan 2017
Published online: 30 Oct 2017 *