Study on control and optimization of soft capsule dropping pills based on intelligent method

Abstract

This paper takes soft capsule dropping pills pharmaceutical production process as the research object. In order to improve the yield of soft capsule dropping pills and its stability of product quality, the modeling and optimizing control are studied based on intelligent control, data-driven modeling and intelligent optimizing algorithms. Firstly, the soft capsule dropping pills pharmaceutical production process is analyzed systematically and hierarchical control architecture is proposed. On this basis, aiming at the problems of the process and the different characteristics of the subsystems, design the appropriate control strategy based on intelligent method to achieve better control results. In the end, on the basis of the completion of various sub-systems modeling and optimizing control, the process of soft capsule dropping pills product quality modeling and optimizing were studied based on LSSVM (least squares support vector machine), AHP (Analysis hierarchy process) and PSO (particle swarm optimization) algorithm. The proposed method can improve the product quality and productivity of the soft capsule dropping pills process.