Stability-Oriented Prediction Horizons Design of Generalized Predictive Control for DC/DC Boost Converter

TL;DR

This paper presents a stability-oriented method for designing prediction horizons in generalized predictive control of DC/DC boost converters, ensuring system stability while reducing computational load.

Contribution

It introduces a rigorous boundary-based prediction horizon design approach that improves stability and computational efficiency over traditional empirical methods.

Findings

The proposed method guarantees system stability.

It reduces computational burden by 10-20%.

Experimental validation confirms effectiveness.

Abstract

This paper introduces a novel approach in designing prediction horizons on a generalized predictive control for a DC/DC boost converter. This method involves constructing a closed-loop system model and assessing the impact of different prediction horizons on system stability. In contrast to conventional design approaches that often rely on empirical prediction horizon selection or incorporate non-linear observers, the proposed method establishes a rigorous boundary for the prediction horizon to ensure system stability. This approach facilitates the selection of an appropriate prediction horizon while avoiding excessively short horizons that can lead to instability and preventing the adoption of unnecessarily long horizons that would burden the controller with high computational demands. Finally, the accuracy of the design method has been confirmed through experimental testing. Moreover, it has been demonstrated that the prediction horizon determined by this method reduces the computational burden by 10\%-20\% compared to the empirically selected prediction horizon.