Optimization of electrospinning process using intelligent control systems

Abstract

This study describes the application of intelligent control systems in electrospinning engineering as well as to use these approaches for optimizing processing conditions. A multi-objective optimization method based on gene algorithm (GA) has been proposed for the design and control of electrospinning process. The processing parameters including Polyvinyl alcohol (PVA) solution concentration, applied voltage, spinning distance and volume flow rate were used as design variables and were mathematically related with the electrospun fiber properties (fiber diameter and its distribution) using gene expression programming (GEP) technique. Nonlinear mathematical functions were derived based on the processing parameters. Afterward, using a multi-objective optimization technique based on gene algorithm, optimal conditions were found in such a way that, mean electrospun fiber diameter and its distribution to be minimized.