Learning Discrete-Time Uncertain Nonlinear Systems With Probabilistic Safety and Stability Constraints

Learning Discrete-Time Uncertain Nonlinear Systems With Probabilistic Safety and Stability Constraints

This paper presents a discrete-time dynamical system model learning method from demonstration while providing probabilistic guarantees on the safety and stability of the learned model. The controlled dynamic model of a discrete-time system with a zero-mean Gaussian process noise is approximated usin...

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Bibliographic Details
Main Authors: Iman Salehi, Tyler Taplin, Ashwin P. Dani
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Open Journal of Control Systems
Subjects:
Discrete-time control barrier function
extreme learning machine
safe model learning
Online Access:https://ieeexplore.ieee.org/document/9926168/

Internet

https://ieeexplore.ieee.org/document/9926168/

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