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Ruigang Wang
Ruigang Wang
Dirección de correo verificada de sydney.edu.au
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Citado por
Citado por
Año
Lipschitz bounded equilibrium networks
M Revay, R Wang, IR Manchester
arXiv preprint arXiv:2010.01732, 2020
622020
Dissipativity based distributed economic model predictive control for residential microgrids with renewable energy generation and battery energy storage
X Zhang, J Bao, R Wang, C Zheng, M Skyllas-Kazacos
Renewable Energy 100, 18-34, 2017
622017
A convex parameterization of robust recurrent neural networks
M Revay, R Wang, IR Manchester
IEEE Control Systems Letters 5 (4), 1363-1368, 2020
552020
Recurrent equilibrium networks: Flexible dynamic models with guaranteed stability and robustness
M Revay, R Wang, IR Manchester
IEEE Transactions on Automatic Control, 2023
492023
Distributed economic MPC with separable control contraction metrics
R Wang, IR Manchester, J Bao
IEEE control systems letters 1 (1), 104-109, 2017
322017
Direct parameterization of lipschitz-bounded deep networks
R Wang, I Manchester
International Conference on Machine Learning, 36093-36110, 2023
312023
Reduced-order nonlinear observers via contraction analysis and convex optimization
B Yi, R Wang, IR Manchester
IEEE Transactions on Automatic Control 67 (8), 4045-4060, 2021
302021
Recurrent equilibrium networks: Unconstrained learning of stable and robust dynamical models
M Revay, R Wang, IR Manchester
2021 60th IEEE Conference on Decision and Control (CDC), 2282-2287, 2021
252021
A data-centric predictive control approach for nonlinear chemical processes
R Wang, J Bao, Y Yao
Chemical Engineering Research and Design 142, 154-164, 2019
192019
Fault diagnosis based on dissipativity property
Q Lei, R Wang, J Bao
Computers & Chemical Engineering 108, 360-371, 2018
192018
Distributed plantwide control based on differential dissipativity
R Wang, J Bao
International Journal of Robust and Nonlinear Control 27 (13), 2253-2274, 2017
172017
A differential Lyapunov-based tube MPC approach for continuous-time nonlinear processes
R Wang, J Bao
Journal of Process Control 83, 155-163, 2019
162019
Robust distributed control of plantwide processes based on dissipativity
Y Yan, R Wang, J Bao, C Zheng
Journal of Process Control 77, 48-60, 2019
162019
Learning over all stabilizing nonlinear controllers for a partially-observed linear system
R Wang, NH Barbara, M Revay, IR Manchester
IEEE Control Systems Letters 7, 91-96, 2022
142022
Virtual control contraction metrics: Convex nonlinear feedback design via behavioral embedding
R Wang, R Tóth, PJW Koelewijn, IR Manchester
International Journal of Robust and Nonlinear Control, 2020
142020
A self-interested distributed economic model predictive control approach to battery energy storage networks
R Wang, X Zhang, J Bao
Journal of Process Control 73, 9-18, 2019
142019
Contraction-based methods for stable identification and robust machine learning: a tutorial
IR Manchester, M Revay, R Wang
2021 60th IEEE Conference on Decision and Control (CDC), 2955-2962, 2021
122021
A comparison of LPV gain scheduling and control contraction metrics for nonlinear control
R Wang, R Tóth, IR Manchester
IFAC-PapersOnLine 52 (28), 44-49, 2019
122019
Differential dissipativity based distributed MPC for flexible operation of nonlinear plantwide systems
RJ McCloy, R Wang, J Bao
Journal of Process Control 97, 45-58, 2021
112021
Continuous-time dynamic realization for nonlinear stabilization via control contraction metrics
R Wang, IR Manchester
2020 American Control Conference (ACC), 1619-1624, 2020
102020
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