Zobrazeno 1 - 10
of 69
pro vyhledávání: '"Cheng, Yikun"'
Safe and Efficient Reinforcement Learning Using Disturbance-Observer-Based Control Barrier Functions
Safe reinforcement learning (RL) with assured satisfaction of hard state constraints during training has recently received a lot of attention. Safety filters, e.g., based on control barrier functions (CBFs), provide a promising way for safe RL via mo
Externí odkaz:
http://arxiv.org/abs/2211.17250
Publikováno v:
In Powder Technology 1 August 2024 444
Publikováno v:
Robotics 2024, 13, 99
This paper presents an approach to trajectory-centric learning control based on contraction metrics and disturbance estimation for nonlinear systems subject to matched uncertainties. The approach uses deep neural networks to learn uncertain dynamics
Externí odkaz:
http://arxiv.org/abs/2112.08222
Publikováno v:
In Talanta 1 June 2024 273
Publikováno v:
In Microchemical Journal May 2024 200
Publikováno v:
In Journal of Colloid And Interface Science 15 April 2024 660:166-176
A reinforcement learning (RL) policy trained in a nominal environment could fail in a new/perturbed environment due to the existence of dynamic variations. Existing robust methods try to obtain a fixed policy for all envisioned dynamic variation scen
Externí odkaz:
http://arxiv.org/abs/2106.02249
Publikováno v:
In Chemical Engineering Science 5 March 2024 285
Publikováno v:
In Journal of Colloid And Interface Science March 2024 657:664-671
Autor:
Jiang, Rong, Cheng, Yikun, Wang, Tianshuo, Zhu, Youqi, Cao, Chuanbao, Ma, Xiaojun, Liu, Guohan, Chen, Long
Publikováno v:
In International Journal of Hydrogen Energy 2 January 2024 49 Part A:647-657