Linear Algebra-Based Internal Model Control Strategies for Non-Minimum Phase Systems: Design and Evaluation

Abstract

This paper addresses the challenge of trajectory tracking in non-minimum-phase systems,which are known for their limitations in performance and stability within process control.The primary objective is to evaluate the feasibility of using linear-algebra-based controlstrategies to achieve precise tracking in such systems. The primary hypothesis is thatinternal model-based compensators can transform non-minimum-phase behavior intoequivalent minimum-phase dynamics, thereby enabling the application of linear algebratechniques for controller design. To validate this approach, both simulation and experimentaltests are conducted, first with a Continuous Stirred Tank Reactor (CSTR) model andthen with the TCLab educational platform. The results show that the proposed methodeffectively achieves robust trajectory tracking, even in the presence of external disturbancesand sensor noise. The primary contribution of this work is to demonstrate that internalmodel-based compensation enables the application of linear control methods to a class ofsystems that are typically considered challenging to control. This not only simplifies thedesign process but also enhances control performance, highlighting the practical relevanceand applicability of the approach for real-world non-minimum-phase systems processes.