MEASUREMENT OF NONLINEARITY IN CHEMICAL PROCESS-CONTROL SYSTEMS - THESTEADY-STATE MAP

Most chemical processes exhibit some degree of nonlinearity, and when selecting an appropriate controller design approach it is important to understand the extent of this nonlinearity. In this paper a quantitat ive measure of steady-state process nonlinearity is proposed. Drawing from results for nonlinear regression, the curvature is decomposed int o tangential and normal components. It is shown that the tangential cu rvature can be reduced or eliminated by transforming the control input s, whereas the normal curvature can be reduced or eliminated only by a combination of state feedback and transformations. The problem of sca ling is addressed by identifying a ''region of interest'', and scale-i ndependent measures of curvature are proposed. Nonlinearity is measure d both as root mean squared curvature and directional curvature. The i mportance of curvature in the forward and inverse steady-state maps is discussed, and a transformation suggested by the curvature arrays is presented. This transformation reduces the static nonlinearity in the process, and can be used to improve the controller performance. Applic ation of the proposed techniques is illustrated using chemical process examples.