On convexity and quasiconvexity of an on-line identification formulation

A method based on non-linear regression has been proposed by Toh and Devana than (1996) to perform closed-loop process identification under naturally o ccurring load disturbances. The significance of this method includes relaxa tion of an important assumption on the knowledge of the input excitation so urce, given a stable controller which is to be improved. While not aiming t o identify a precise model as in classical design, this method uses an appr oximate process model for on-line identification. This serves as a basis fo r controller refinement, without having to interrupt the process operation for identification test. In this paper, we present a refined formulation an d then perform convexity analysis and quasiconvexity analysis on this refin ed formulation. We show that these results can be utilized to obtain conver gence independent of the initial estimates. Applicability of the identifica tion for controller tuning is also demonstrated using a process with an unk nown model.