# Enhancement of Energy-Based Swing-Up Controller via Entropy Search

## TL;DR

This paper enhances an energy-based swing-up controller for a rotary inverted pendulum by applying Bayesian optimization with Entropy Search, resulting in improved performance across different initial conditions.

## Contribution

It introduces a novel application of Entropy Search Bayesian optimization to tune parameters of an energy-based swing-up controller for the Furuta pendulum.

## Key findings

- Optimal controller outperforms nominal controller in simulations.
- Performance improvements observed across various initial conditions.
- Bayesian optimization effectively finds suitable controller parameters.

## Abstract

An energy based approach for stabilizing a mechanical system has offered a simple yet powerful control scheme. However, since it does not impose such strong constraints on parameter space of the controller, finding appropriate parameter values for an optimal controller is known to be hard. This paper intends to generate an optimal energy-based controller for swinging up a rotary inverted pendulum, also known as the Furuta pendulum, by applying the Bayesian optimization called Entropy Search. Simulations and experiments show that the optimal controller has an improved performance compared to a nominal controller for various initial conditions.