An immune-enhanced unfalsified controller for a high-speed spinning process

Abstract

One key process in data-driven methodology is how to use the data easily and efficiently. In this paper, an immune-enhanced unfalsified controller (IEUC) is proposed to act as an efficient process to deal with data. The IEUC consists of two parts, the first part is a unfalsified controller deriving from data-driven methodology; the second part is an immune feedback controller inspired from biologic intelligent methodology. In order to examine control effectiveness of the IEUC, we apply it to a complex plant in high-speed spinning model and compare it with a simple unfalsified control scheme. Simulation results demonstrate that the IEUC can decrease system overshoot as well as reduce rising time successfully and effectively. © 2011 Springer-Verlag Berlin Heidelberg.