Identification, Uncertain Modelling, and Robust Control of Embedded Systems

Abstract

This paper presents a methodology embodying identification procedures, uncertain modeling, and robust control design for embedded multivariable control systems. Concerning the identification, this methodology involved the determination of probabilistic uncertainty bounds for multivariable plants based on the black-box or gray-box identification. The bounds obtained were used in the derivation of an uncertain model in the form of upper Linear Fractional Transformation (LFT). This model was then utilized in the robust control design using μ-synthesis. The problems arising on the different design stages were illustrated by an example presenting the embedded robust control of a two-input two-output analog model. The plant was identified by using black-box or gray-box identification methods, which provided the necessary information to develop the corresponding uncertainty models. Two discrete-time robust controllers relevant to the two types of identification were designed and embedded into the physical system. Simulation results of the embedded closed-loop system were compared with experimental results obtained by using the robust controllers.