OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!
If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.
Requested Article:
Control of Switched Boolean Control Networks by State Feedback
Amol Yerudkar, Carmen Del Vecchio, Luigi Glielmo
(2019), pp. 1999-2004
Closed Access | Times Cited: 9
Amol Yerudkar, Carmen Del Vecchio, Luigi Glielmo
(2019), pp. 1999-2004
Closed Access | Times Cited: 9
Showing 9 citing articles:
Feedback stabilization control design for switched Boolean control networks
Amol Yerudkar, Carmen Del Vecchio, Luigi Glielmo
Automatica (2020) Vol. 116, pp. 108934-108934
Closed Access | Times Cited: 62
Amol Yerudkar, Carmen Del Vecchio, Luigi Glielmo
Automatica (2020) Vol. 116, pp. 108934-108934
Closed Access | Times Cited: 62
Reinforcement Learning Approach to Feedback Stabilization Problem of Probabilistic Boolean Control Networks
Antonio Acernese, Amol Yerudkar, Luigi Glielmo, et al.
IEEE Control Systems Letters (2020), pp. 1-1
Closed Access | Times Cited: 47
Antonio Acernese, Amol Yerudkar, Luigi Glielmo, et al.
IEEE Control Systems Letters (2020), pp. 1-1
Closed Access | Times Cited: 47
Output Tracking Control Design of Switched Boolean Control Networks
Amol Yerudkar, Carmen Del Vecchio, Luigi Glielmo
IEEE Control Systems Letters (2019) Vol. 4, Iss. 2, pp. 355-360
Closed Access | Times Cited: 31
Amol Yerudkar, Carmen Del Vecchio, Luigi Glielmo
IEEE Control Systems Letters (2019) Vol. 4, Iss. 2, pp. 355-360
Closed Access | Times Cited: 31
Sampled-data Control of Probabilistic Boolean Control Networks: A Deep Reinforcement Learning Approach
Amol Yerudkar, Evangelos Chatzaroulas, Carmen Del Vecchio, et al.
Information Sciences (2022) Vol. 619, pp. 374-389
Open Access | Times Cited: 16
Amol Yerudkar, Evangelos Chatzaroulas, Carmen Del Vecchio, et al.
Information Sciences (2022) Vol. 619, pp. 374-389
Open Access | Times Cited: 16
Model-Free Self-Triggered Control Co-Design for Probabilistic Boolean Control Networks
Antonio Acernese, Amol Yerudkar, Luigi Glielmo, et al.
IEEE Control Systems Letters (2020) Vol. 5, Iss. 5, pp. 1639-1644
Closed Access | Times Cited: 23
Antonio Acernese, Amol Yerudkar, Luigi Glielmo, et al.
IEEE Control Systems Letters (2020) Vol. 5, Iss. 5, pp. 1639-1644
Closed Access | Times Cited: 23
Disturbance decoupling control design for Boolean control networks: a Boolean algebra approach
Kisan Sarda, Amol Yerudkar, Carmen Del Vecchio
IET Control Theory and Applications (2020) Vol. 14, Iss. 16, pp. 2339-2347
Closed Access | Times Cited: 20
Kisan Sarda, Amol Yerudkar, Carmen Del Vecchio
IET Control Theory and Applications (2020) Vol. 14, Iss. 16, pp. 2339-2347
Closed Access | Times Cited: 20
Sampled-Data Set Stabilization of Switched Boolean Control Networks
Amol Yerudkar, Carmen Del Vecchio, Luigi Glielmo
IFAC-PapersOnLine (2020) Vol. 53, Iss. 2, pp. 6139-6144
Open Access | Times Cited: 14
Amol Yerudkar, Carmen Del Vecchio, Luigi Glielmo
IFAC-PapersOnLine (2020) Vol. 53, Iss. 2, pp. 6139-6144
Open Access | Times Cited: 14
Reference trajectory output tracking for Boolean control networks with controls in output
Zejiao Liu, Yu Wang, Yang Liu, et al.
Mathematical Modelling and Control (2023) Vol. 3, Iss. 3, pp. 256-266
Open Access | Times Cited: 1
Zejiao Liu, Yu Wang, Yang Liu, et al.
Mathematical Modelling and Control (2023) Vol. 3, Iss. 3, pp. 256-266
Open Access | Times Cited: 1
Model-free Self-triggered Control Co-design for Probabilistic Boolean Control Networks
Antonio Acernese, Amol Yerudkar, Luigi Glielmo, et al.
2022 American Control Conference (ACC) (2021), pp. 380-385
Closed Access
Antonio Acernese, Amol Yerudkar, Luigi Glielmo, et al.
2022 American Control Conference (ACC) (2021), pp. 380-385
Closed Access
