| 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 | 62 | 2017 |
| Lipschitz bounded equilibrium networks M Revay, R Wang, IR Manchester arXiv preprint arXiv:2010.01732, 2020 | 60 | 2020 |
| A convex parameterization of robust recurrent neural networks M Revay, R Wang, IR Manchester IEEE Control Systems Letters 5 (4), 1363-1368, 2020 | 54 | 2020 |
| Recurrent equilibrium networks: Flexible dynamic models with guaranteed stability and robustness M Revay, R Wang, IR Manchester IEEE Transactions on Automatic Control, 2023 | 48 | 2023 |
| Distributed economic MPC with separable control contraction metrics R Wang, IR Manchester, J Bao IEEE control systems letters 1 (1), 104-109, 2017 | 32 | 2017 |
| Direct parameterization of lipschitz-bounded deep networks R Wang, I Manchester International Conference on Machine Learning, 36093-36110, 2023 | 30 | 2023 |
| 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 | 30 | 2021 |
| 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 | 23 | 2021 |
| 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 | 19 | 2019 |
| Fault diagnosis based on dissipativity property Q Lei, R Wang, J Bao Computers & Chemical Engineering 108, 360-371, 2018 | 18 | 2018 |
| Distributed plantwide control based on differential dissipativity R Wang, J Bao International Journal of Robust and Nonlinear Control 27 (13), 2253-2274, 2017 | 17 | 2017 |
| A differential Lyapunov-based tube MPC approach for continuous-time nonlinear processes R Wang, J Bao Journal of Process Control 83, 155-163, 2019 | 16 | 2019 |
| 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 | 16 | 2019 |
| 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 | 14 | 2019 |
| 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 | 13 | 2022 |
| 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 | 13 | 2020 |
| 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 | 12 | 2021 |
| 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 | 12 | 2019 |
| 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 | 11 | 2021 |
| Continuous-time dynamic realization for nonlinear stabilization via control contraction metrics R Wang, IR Manchester 2020 American Control Conference (ACC), 1619-1624, 2020 | 10 | 2020 |
Jie BaoProfessor, School of Chemical Engineering, The University of New South Wales在 unsw.edu.au 的电子邮件经过验证
