ICONS 2019 Paper Abstract

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Paper ThB2SP.3

Verdier, Cees (Delft University of Technology), Babuska, Robert (Delft University of Technology), Shyrokau, Barys (Nanyang Technological University), Mazo Jr, Manuel (TU Delft)

Near Optimal Control with Reachability and Safety Guarantees

Scheduled for presentation during the Regular Session "Learning and Control" (ThB2SP), Thursday, August 22, 2019, 16:40−17:00,

5th IFAC International Conference on Intelligent Control and Automation Sciences, August 21-23, 2019, Queen’s University Belfast, Northern Ireland

This information is tentative and subject to change. Compiled on November 29, 2021

Keywords Reinforcement learning, Computer-aided design tools, Evolutionary/genetic algorithms for control

Abstract

Control systems designed via learning methods, aiming at quasi-optimal solutions, typically lack stability and performance guarantees. We propose a method to construct a near-optimal control law by means of model-based reinforcement learning and subsequently verifying the reachability and safety of the closed-loop control system through an automatically synthesized Lyapunov barrier function. We demonstrate the method on the control of an anti-lock braking system. Here the optimal control synthesis is used to minimize the braking distance, whereas we use verification to show guaranteed convergence to standstill and formally bound the braking distance.

 

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