Identification of Uncertainty Bounds for Robust Control with Applications to a Fixed Bed Reactor

Abstract

A model-based robust controller is designed for a packed bed methanation reactor. To accomplish this objective, model uncertainty bounds are identified from experimental data. A physically motivated methodology of regions mapping was developed to compute the uncertainty bounds in the complex plane. This technique is compared to other existing nonparametric approaches for a simple nonlinear system and is shown to produce a more accurate description of the model uncertainty for the purpose of robust control design. This regions-mapping approach is then applied to a fixed bed reactor and uncertainty bounds are computed. A robust controller with a single adjustable parameter is designed for the reactor using internal model control (IMC) theory. The computed uncertainty bounds are experimentally validated using the IMC controller.