Nonlinear Controller Design with Prediction Horizon Time Reduction Applied to Unstable CSTR System

TL;DR

This paper introduces new nonlinear controller design methods that significantly enlarge terminal regions and reduce prediction horizon time for stabilizing an unstable CSTR system, enhancing control efficiency.

Contribution

It proposes arbitrary controller and LQR-based approaches that enlarge terminal regions, enabling shorter prediction horizons compared to existing conservative methods.

Findings

Terminal regions are 45 and 412 times larger with proposed methods.

Significant reduction in prediction and control horizon times.

Demonstrated effectiveness on an unstable CSTR system.

Abstract

Ensuring nominal asymptotic stability of the Nonlinear Model Predictive Control controller is not trivial. Stabilizing ingredients such as terminal penalty term and terminal region are crucial in establishing the asymptotic stability. Current work presents alternate approaches namely arbitrary controller based approach and linear quadratic regulator based approach, which provide larger degrees of freedom for enlarging the terminal region as against conservative approaches from the literature. Efficacy of the proposed approaches is demonstrated using benchmark two state continuous stirrer tank reactor system around an unstable operating point. Terminal regions obtained using the arbitrary controller based approach and linear quadratic regulator based approach are approximately 45 and 412 times larger by area measure when compared to the largest terminal region obtained using the approach from the literature. As a result, there is significant reduction in the prediction and control horizon time.