Data-Driven Multi-Modal Learning Model Predictive Control

Fionna B. Kopp; Francesco Borrelli

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arXiv · 2407.06313

Data-Driven Multi-Modal Learning Model Predictive Control

Fionna B. Kopp·Francesco Borrelli

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Abstract

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.

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Fionna B. Kopp, Francesco Borrelli. 2024-07-08. Data-Driven Multi-Modal Learning Model Predictive Control. https://arxiv.org/abs/2407.06313

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