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arXiv · 2202.09557

Safe Control Synthesis with Uncertain Dynamics and Constraints

Kehan Long·Vikas Dhiman·Melvin Leok·Jorge Cortés·Nikolay Atanasov
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Abstract

This paper considers safe control synthesis for dynamical systems with either probabilistic or worst-case uncertainty in both the dynamics model and the safety constraints. We formulate novel probabilistic and robust (worst-case) control Lyapunov function (CLF) and control barrier function (CBF) constraints that take into account the effect of uncertainty in either case. We show that either the probabilistic or the robust (worst-case) formulation leads to a second-order cone program (SOCP), which enables efficient safe and stable control synthesis. We evaluate our approach in PyBullet simulations of an autonomous robot navigating in unknown environments and compare the performance with a baseline CLF-CBF quadratic programming approach.

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Kehan Long, Vikas Dhiman, Melvin Leok, Jorge Cortés, Nikolay Atanasov. 2022-02-19. Safe Control Synthesis with Uncertain Dynamics and Constraints. https://doi.org/10.1109/lra.2022.3182544

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