An approach to data-driven design of feedback control systems with embedded residual generation

Abstract

Motivated by the increasing needs in the process industry for designing fault tolerant feedback control systems based on process data, data-driven design of feedback control systems with embedded residual generation is addressed. For this purpose, an extended internal model control (EIMC) structure aiming at accessing the residuals embedded in control loop is first proposed. Based on the identification of the so-called parity subspace and a well-established mapping between the parity vector and the solution of the Luenberger equations, a direct design scheme of EIMC from process data is developed. The achieved results are illustrated by an academic example.