Optimal design of QFT controller for pneumatic servo actuator system using multi-objective genetic algorithm Online publication date: Fri, 14-Feb-2020
by Nitish Katal; Shiv Narayan
International Journal of Advanced Intelligence Paradigms (IJAIP), Vol. 15, No. 2, 2020
Abstract: Loop shaping is the principle step for synthesising the quantitative feedback theory (QFT) based robust controllers. The controller assures performance robustness in the presence of plant uncertainties. This paper explores a template and bounds free approach for the automated synthesis of low order fixed structure QFT controller for a highly uncertain pneumatic servo actuator system. In this work, the loop-shaping problem has been posed as a multi-objective optimisation problem and solved using the multi-objective variant of the genetic algorithm. At the end of the design process, a set of Pareto optimal solutions (POS) are obtained, to aid the decision maker in choosing an ideal solution from the POS, use of level diagrams has been explored. The simulation of the results and time and frequency domain analysis has been carried out using MATLAB and the results obtained clearly unveil that the designed QFT controller offers robust behaviour over a range of plant's parametric uncertainty.
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