Publication detail

Genetic Optimization Meets Visualization: Multi-objective LQR Tuning for the Furuta Pendulum

HOLOUBEK, T. ŠKRABÁNEK, P.

English title

Genetic Optimization Meets Visualization: Multi-objective LQR Tuning for the Furuta Pendulum

Type

Paper in proceedings (conference paper)

Language

en

Original abstract

This paper presents a visualization-guided approach to multi-objective tuning of Linear-Quadratic Regulator (LQR) controllers, demonstrated on the stabilization of the Furuta pendulum. A scalarized fitness function combining settling time and peak deviation is optimized using a Genetic Algorithm over a range of trade-off parameters. The resulting Pareto front is visualized in objective space, and representative gain matrices are shown along the front to support interpretable controller selection. Unlike conventional tuning methods that yield a single solution, the proposed framework provides a compact and intuitive summary of the entire trade-off space. This enhances decision-making in control design and is applicable to a broad class of systems.

Keywords in English

Furuta Pendulum | Genetic Algorithm | Linear Quadratic Regulator | Multi-objective Optimization

Released

2025-10-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

ISBN

9781665457873

Book

Edpe 2025 37th International Conference on Electrical Drives and Power Electronics and 12th Joint Croatia Slovakia Conference

Pages count

5

BIBTEX


@inproceedings{BUT200134,
  author="Tomáš {Holoubek} and Pavel {Škrabánek}",
  title="Genetic Optimization Meets Visualization: Multi-objective LQR Tuning for the Furuta Pendulum",
  booktitle="Edpe 2025 37th International Conference on Electrical Drives and Power Electronics and 12th Joint Croatia Slovakia Conference",
  year="2025",
  pages="5",
  publisher="Institute of Electrical and Electronics Engineers Inc.",
  doi="10.1109/EDPE66853.2025.11224248",
  isbn="9781665457873"
}