Enhancement of Energy-Based Swing-Up Controller via Entropy Search
Machine Learning
2019-04-04 v2 Systems and Control
Optimization and Control
Machine Learning
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.
Keywords
Cite
@article{arxiv.1904.01214,
title = {Enhancement of Energy-Based Swing-Up Controller via Entropy Search},
author = {Chang Sik Lee and Dong Eui Chang},
journal= {arXiv preprint arXiv:1904.01214},
year = {2019}
}
Comments
6 pages, 2019 Asian Control Conference