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OpenAlex Citation Counts

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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:

Fusion of Machine Learning and MPC under Uncertainty: What Advances Are on the Horizon?
Ali Mesbah, Kim P. Wabersich, Angela P. Schoellig, et al.
2022 American Control Conference (ACC) (2022), pp. 342-357
Closed Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

Data-Driven Control Based on the Behavioral Approach: From Theory to Applications in Power Systems
Ivan Markovsky, Linbin Huang, Florian Dörfler
IEEE Control Systems (2023) Vol. 43, Iss. 5, pp. 28-68
Closed Access | Times Cited: 38
Integrated learning‐based estimation and nonlinear predictive control of an ammonia synthesis reactor
Amirsalar Bagheri, Thiago Oliveira Cabral, Davood Babaei Pourkargar
AIChE Journal (2025)
Closed Access | Times Cited: 1
Data-Driven Safety Filters: Hamilton-Jacobi Reachability, Control Barrier Functions, and Predictive Methods for Uncertain Systems
Kim P. Wabersich, Andrew J. Taylor, Jason J. Choi, et al.
IEEE Control Systems (2023) Vol. 43, Iss. 5, pp. 137-177
Closed Access | Times Cited: 23
Gradient-Based Framework for Bilevel Optimization of Black-Box Functions: Synergizing Model-Free Reinforcement Learning and Implicit Function Differentiation
Thomas Banker, Ali Mesbah
Industrial & Engineering Chemistry Research (2025) Vol. 64, Iss. 5, pp. 2831-2844
Open Access
Simultaneous multistep transformer architecture for model predictive control
Junho Park, Mohammad Reza Babaei, Samuel Arce Muñoz, et al.
Computers & Chemical Engineering (2023) Vol. 178, pp. 108396-108396
Closed Access | Times Cited: 16
Learning‐based adaptive‐scenario‐tree model predictive control with improved probabilistic safety using robust Bayesian neural networks
Yajie Bao, Kimberly J. Chan, Ali Mesbah, et al.
International Journal of Robust and Nonlinear Control (2022) Vol. 33, Iss. 5, pp. 3312-3333
Open Access | Times Cited: 17
Performance Guaranteed MPC Policy Approximation via Cost Guided Learning
Chenchen Zhou, Yi Cao, Shuang‐Hua Yang
IEEE Control Systems Letters (2024) Vol. 8, pp. 346-351
Closed Access | Times Cited: 2
A Tutorial on Derivative-Free Policy Learning Methods for Interpretable Controller Representations
Joel A. Paulson, Farshud Sorourifar, Ali Mesbah
2022 American Control Conference (ACC) (2023) Vol. 29, pp. 1295-1306
Closed Access | Times Cited: 7
Data-driven auto-tuning strategy for RTO-MPC based on Bayesian optimization
Lingzhi Zhang, Lei Xie, Hongye Su, et al.
Computers & Chemical Engineering (2024) Vol. 187, pp. 108743-108743
Open Access | Times Cited: 1
Data-Driven Predictive Control and MPC: Do we achieve optimality?
Aditi Anand, Shrutika S. Sawant, Dirk Reinhardt, et al.
IFAC-PapersOnLine (2024) Vol. 58, Iss. 15, pp. 73-78
Open Access | Times Cited: 1
Towards Personalized Plasma Medicine via Data-Efficient Adaptation of Fast Deep Learning-based MPC Policies
Kimberly J. Chan, Georgios Makrygiorgos, Ali Mesbah
2022 American Control Conference (ACC) (2023)
Open Access | Times Cited: 4
Model-Free Data-Driven Predictive Control Using Reinforcement Learning
Shambhuraj Sawant, Dirk Reinhardt, Arash Bahari Kordabad, et al.
(2023) Vol. 2, pp. 4046-4052
Closed Access | Times Cited: 3
An Improved Data Augmentation Scheme for Model Predictive Control Policy Approximation
Dinesh Krishnamoorthy
IEEE Control Systems Letters (2023) Vol. 7, pp. 1867-1872
Open Access | Times Cited: 2
Learning-based motion control of a rover on unknown ground
Niklas Baldauf, Alen Turnwald, Toni Lubiniecki, et al.
(2023)
Open Access | Times Cited: 2
Learning Iterative Solvers for Accurate and Fast Nonlinear Model Predictive Control via Unsupervised Training
Lukas Lüken, Sergio Lucia
2022 European Control Conference (ECC) (2024), pp. 1843-1850
Closed Access
Lifelong Learning for Monitoring and Adaptation of Data-Based Dynamical Models: A Statistical Process Control Approach
Laura Boca de Giuli, Alessio La Bella, Giuseppe De Nicolao, et al.
2022 European Control Conference (ECC) (2024), pp. 947-952
Closed Access
Learning-based Distributed Model Predictive Control with State-dependent Uncertainty Using Neural Network
Junbo Tong, Shuhan Du, Wenhui Fan
2022 American Control Conference (ACC) (2024) Vol. 32, pp. 911-918
Closed Access
Towards learning-based trajectory tracking control for a planetary exploration rover: Adaptive model predictive control
Niklas Baldauf, Kristin Lakatos, Alexander Meinert, et al.
2022 26th International Conference on System Theory, Control and Computing (ICSTCC) (2024), pp. 1-6
Closed Access
A tutorial review of machine learning-based model predictive control methods
Zhe Wu, Panagiotis D. Christofides, Wanlu Wu, et al.
Reviews in Chemical Engineering (2024)
Open Access
Adaptive Uncertainty Quantification for Scenario-based Control Using Meta-learning of Bayesian Neural Networks
Yajie Bao, Javad Mohammadpour Velni
IFAC-PapersOnLine (2024) Vol. 58, Iss. 28, pp. 486-491
Open Access
Deterministic Safety Guarantees for Learning-Based Control of Monotone Nonlinear Systems Under Uncertainty
Joshua Adamek, Moritz Heinlein, Lukas Lüken, et al.
IEEE Control Systems Letters (2024) Vol. 8, pp. 1030-1035
Open Access
Development of algorithms for augmenting and replacing conventional process control using reinforcement learning
Daniel Beahr, Debangsu Bhattacharyya, Douglas A. Allan, et al.
Computers & Chemical Engineering (2024) Vol. 190, pp. 108826-108826
Closed Access
Uncertainty Estimation of NMPC Horizon employing Neural Networks & MC-dropout in Safety-Critical Applications with Barrier Functions
Spyridon Syntakas, Kostas Vlachos
(2023)
Open Access | Times Cited: 1
Iterative learning-based model predictive control for mobile robots in space applications
Niklas Baldauf, Alen Turnwald
(2023), pp. 434-439
Closed Access | Times Cited: 1
Uncertainty Quantification for Learning-based MPC using Weighted Conformal Prediction
Kong Yao Chee, M. Ani Hsieh, George J. Pappas
(2023) Vol. 2, pp. 342-349
Closed Access | Times Cited: 1
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