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arXiv · 2311.08496

A Robust, Efficient Predictive Safety Filter

Wenceslao Shaw Cortez·Jan Drgona·Draguna Vrabie·Mahantesh Halappanavar
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Abstract

In this paper, we propose a novel predictive safety filter that is robust to bounded perturbations and is implemented in an even-triggered fashion to reduce online computation. The proposed safety filter extends upon existing work to reject disturbances for discrete-time, time-varying nonlinear systems with time-varying constraints. The safety filter is based on novel concepts of robust, discrete-time barrier functions and can be used to filter any control law. Here, we use the safety filter in conjunction with Differentiable Predictive Control (DPC) as a promising offline learning-based policy optimization method. The approach is demonstrated on a two-tank system, building, and single-integrator example.

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Wenceslao Shaw Cortez, Jan Drgona, Draguna Vrabie, Mahantesh Halappanavar. 2023-11-14. A Robust, Efficient Predictive Safety Filter. https://arxiv.org/abs/2311.08496

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