Adaptive Bayesian Optimization for High-Precision Motion Systems

arXiv:2404.14602v1 Announce Type: cross
Abstract: Controller tuning and parameter optimization are crucial in system design to improve closed-loop system performance. Bayesian optimization has been established as an efficient model-free controller tuning and adaptation method. However, Bayesian optimization methods are computationally expensive and therefore difficult to use in real-time critical scenarios. In this work, we propose a real-time purely data-driven, model-free approach for adaptive control, by online tuning low-level controller parameters. We base our algorithm on GoOSE, an algorithm for safe …

abstract arxiv bayesian cs.lg cs.ro cs.sy design eess.sy free however loop optimization performance precision real-time systems type work