تقرير
Data-Driven Multi-Modal Learning Model Predictive Control
العنوان: | Data-Driven Multi-Modal Learning Model Predictive Control |
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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 |
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