Modeling, Identification and Validation of Uncertain Systems; Theory and Experiments

University Of California-Santa Barbara, Santa Barbara CA

Investigators

Abstract

The objective of the proposed work is to develop an integrated suite of tools and approaches for the modeling of uncertain systems for feedback control design purposes. Our modeling framework is based upon robust control theory, which is supported by several sophisticated control design methods. These models are in effect set descriptions, where the sets are generated by unknown but bounded dynamic perturbations within the model. These models allow the designer to capture the variety of uncertain behaviors that a physical system will generate. Although this is a powerful and flexible modeling framework, the tools available for modeling physical systems are limited. We address this area in this proposal, with the ultimate goal being the development of a suite of modeling techniques and software tools for control system modeling. Our prior work on model validation for robust control models forms the basis for the work proposed here. This approach has led to tools which allow the designer to experimentally quantify the difference between a physical system and the closest member of a robust control model set. In the area of theoretical model development we propose extending our current model validation approaches to describe non-linear and parametrically varying systems. In the experimental application area, two systems will be studied: control of semiconductor growth rate and composition in a metalorganic vapor deposition (MOCVD) reactor; control of unstable rotating magnetic bearing systems. Both applications have a great deal of industrial relevance, as well as providing challenging testbeds for the theoretical work. In the algorithmic development work, we propose refining structured algorithms to handle the very large problems that arise when applying model validation methods to data driven problems. The strong experimental component has significant wider benefits. The MOCVD experimental system is a nontraditional area for control work and fosters interaction and the exchange of ideas between the control theory community and semiconductor and materials scientists. The experiments are also integrated into engineering course work at UCSB, and are currently used as demonstration examples in undergraduate control courses and graduate level design laboratories.