تقرير
Data-Driven Multi-Modal Learning Model Predictive Control
| العنوان: | Data-Driven Multi-Modal Learning Model Predictive Control |
|---|---|
| المؤلفون: | Kopp, Fionna B., Borrelli, Francesco |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Electrical Engineering and Systems Science - Systems and Control |
| الوصف: | We present a Learning Model Predictive Controller (LMPC) for multi-modal systems performing iterative control tasks. Assuming availability of historical data, our goal is to design a data-driven control policy for the multi-modal system where the current mode is unknown. First, we propose a novel method to select local data for constructing affine time-varying (ATV) models of a multi-modal system in the context of LMPC. Then we present how to build a sampled safe set from multi-modal historical data. We demonstrate the effectiveness of our method through simulation results of automated driving on a friction-varying track. Comment: Submitted to 2024 IEEE Conference on Decision and Control |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2407.06313 |
| رقم الأكسشن: | edsarx.2407.06313 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |