Publications

2025

• Ma, X., Ning, C.*, Du, W., Shi, Y. (2025). Data-Driven Distributionally Robust Mixed-Integer Control through Lifted Control Policy. IEEE Transactions on Automatic Control. DOI: 10.1109/TAC.2025.3558138. [PDF]

• Li, L., Ning, C.*, Pan, G., Zhang, L., Gu, W., Zhao L., Du, W., Shahidehpour, M. (2025). A Risk-Averse Just-In-Time Scheme for Learning Based Operation of Microgrids with Coupled Electricity-Hydrogen-Ammonia under Uncertainties. IEEE Transactions on Sustainable Energy. DOI: 10.1109/TSTE.2025.3561067. [PDF]

• Ning, C.*, Zhao, J., Wang, H. (2025). Learning-Enabled Stochastic Predictive Control for Nonlinear Discrete-Time Step Backward High-Order Fully Actuated Systems. International Journal of Systems Science. [PDF]

• Li, L., Liu, S., Ning, C.* (2025). Data-Driven Distributionally Robust Planning of Electricity-Heat-Hydrogen-Ammonia Microgrid Considering The Electrothermal-Aging Effect of SOEC. Power System Technology, 49(1), 22-31.

• Ma, A., Ning, C.* (2025). Adaptive Distributionally Robust Scheduling for Green Electricity-Hydrogen-Ammonia Coupling Systems. Clean Coal Technology. (Accepted)

• Gao, F., Yang, B., Ning, C., Guan, X. (2025). Virtual Leader-follower based Platooning Under Mixed Traffic: A Data-driven Distributionally Robust MPC Method. IEEE Transactions on Vehicular Technology. DOI: 10.1109/TVT.2025.3561126. [PDF]

2024

• Ma, X., Ning, C.*, Du, W. (2024). Differentiable Distributionally Robust Optimization Layers. International Conference on Machine Learning (ICML), 235, 33880-33901. (CCF-A) [PDF, Code]

• Ma, X., Ning, C.*, Li, L., Qiu, H., Gu, W., Dong, Z. (2024). Bayesian Nonparametric Two-Stage Distributionally Robust Unit Commitment Optimization: From Global Multimodality to Local Trimming-Wasserstein Ambiguity. IEEE Transactions on Power Systems, 39, 6702-6715. [PDF]

• Li, L., Ning, C.*, Qiu, H., Du, W., Dong, Z. (2024). Online Data-Stream-Driven Distributionally Robust Optimal Energy Management for Hydrogen-Based Multi-Microgrids. IEEE Transactions on Industrial Informatics, 20, 4370-4384. [PDF]

• Wang, H., Ning, C.*, Li, L., Zhang, W. (2024). Online-Learning-Based Distributionally Robust Motion Control with Collision Avoidance for Mobile Robots. IEEE International Conference on Robotics and Automation (ICRA), 1241-1246. (CAAI-A)

• Wang, H., Ning, C.* (2024). Online-Learning-Enabled Distributionally Robust Motion Control Via Uncertainty Propagation and Ambiguity Set Compression. 63rd IEEE Conference on Decision and Control (CDC), 4342-4348.

• Li, L., Ning, C.* (2024). Data-Driven Distributionally Robust Electricity-Hydrogen Trading Considering The Carbon Intensity of Hydrogen Production. Asian Control Conference (ASCC), 1444-1449.

• Liu, S., Li, L., Ning, C.* (2024). Optimal Planning of Multi-Energy Systems for Sustainable Ammonia Production Considering Electrothermal-Aging Effect of SOEC. IEEE 22nd International Conference on Industrial Informatics (INDIN), 1-6.

• Zhao J., Wang, H., Ning, C.* (2024). Data-Driven MPC for Uncertain High-Order Fully Actuated Systems. China Automation Congress (CAC), 1267-1271.

• Gu, J., Li, L., Ning, C.* (2024). Optimal Planning of Zero-Carbon Off-Grid Ammonia-Hydrogen-Based Microgrids Considering Hybrid Types of Electrolyzer Modules. Power System and Green Energy Conference (PSGEC), 562-567.

• Qiu, H., Veerasamy, V., Ning, C., Sun, Q., Gooi, H.B. (2024). Two-Stage Robust Optimization for Assessment of PV Hosting Capacity Based on Decision-Dependent Uncertainty. Journal of Modern Power Systems and Clean Energy, 12(6), 2091-2096.

2023

• Ning, C.*, Ma, X. (2023). Data-Driven Bayesian Nonparametric Wasserstein Distributionally Robust Optimization. IEEE Control Systems Letters, 7, 3597-3602.

• Li, L., Ning, C.* (2023). Streaming-Data-Driven Multi-Objective Optimal Operation for Ammonia-based Integrated Energy Chemical Systems: An Event-Triggered Scheme. In 2023 42nd Chinese Control Conference (CCC) (pp. 6632-6637).

• Ma, X., Ning, C.* (2023). Data-Driven Distributionally Robust Planning of Energy Hub Coupled with Carbon Capture Utilization and Storage Facilities. In 2023 42nd Chinese Control Conference (CCC) (pp. 2573-2579).

• Wang, H., Li, L., Ning, C.*. (2023). Provably Safe Deep Learning-Based Offset-Free Model Predictive Control And Its Application to Safety-Critical Autonomous Driving. International Conference on Robotics, Control and Automation Engineering (RCAE). (Accepted)

• Wang, H., Li, L., Ning, C.*. (2023). Safe Deep Learning-Based Offset-Free MPC for Green Hydrogen Injected PEMFC Systems. China Automation Congress (CAC). (Accepted)

• Qiu, H., Gu, W., Ning, C., Lu, X., Liu, P., Wu, Z. (2023). Multistage Mixed-Integer Robust Optimization for Power Grid Scheduling: An Efficient Reformulation Algorithm. IEEE Transactions on Sustainable Energy, 14 (1), 254-271.

• Deng, H., Yang, B., Ning, C., Chen, C., Guan, X. (2023). Distributionally Robust Day-Ahead Scheduling for Power-Traffic Network under A Potential Game Framework. International Journal of Electrical Power & Energy Systems, 147, p.108851.

2022

• Ning, C., You, F. (2022). Deep Learning based Distributionally Robust Joint Chance Constrained Economic Dispatch under Wind Power Uncertainty. IEEE Transactions on Power Systems, 37, 191-203.

• Li, L., Ning, C.* (2022). Integrated Power and Hydrogen Trading in Multi-microgrid Coupled with Offsite Hydrogen Refueling Stations. IEEE Conference on Energy Internet and Energy System Integration (IEEE EI2), (Accepted).

• Ning, C.*, Li, L. (2022). Online Learning Enabled Hierarchical Distributionally Robust Model Predictive Control of Green-Hydrogen Microgrids under Uncertainties. IEEE International Electrical and Energy Conference, 2366-2371. (🏆 Best Paper Award).

• Li, L., Ning, C.*, Qiu H. (2022). Streaming-Data-Driven Distributionally Robust Joint Operation of Multi-Microgrids and Off-Site Hydrogen Refueling Stations under Uncertainties. IEEE International Conference on Innovative Smart Grid Technologies (IEEE ISGT-Asia).

• Ning, C.*, Li, L. (2022). Data-Driven Robust Optimization for Energy Chemical Processes under Uncertainties: A Review and Tutorial. International Conference on Industrial Artificial Intelligence (IAI). (🏆 Best Paper Award).

• Li, L., Ning, C.* (2022). Event-Triggered Online Learning Assisted Distributionally Robust Energy Management of Ammonia-Based Multi-Energy Microgrids. International Conference on Industrial Artificial Intelligence (IAI), (Accepted).

• Cao, J., Yang, B., Zhu, S., Ning, C., Guan, X. (2022). Day-ahead Chance-Constrained Energy Management of Energy Hub: A Distributionally Robust Approach. CSEE Journal of Power and Energy Systems, 8(3), 812-825.

• Qiu, H., Wang, L., Gu, W., Pan, G., Ning, C., Wu, Z., Sun, Q. (2022). Multistage Scheduling of Regional Power Grids Against Sequential Outage and Power Uncertainties. IEEE Transactions on Smart Grid, 13 (6), 4624-4637.

Before 2021

• Ning, C., You, F. (2021). Online Learning Based Risk-Averse Stochastic MPC of Constrained Linear Uncertain Systems. Automatica, 125, 109402.

• Ning, C., You, F. (2021). Data-Driven Ambiguous Joint Chance Constrained Economic Dispatch with Correlated Wind Power Uncertainty. American Control Conference (ACC), 1807-1812.

• Ning, C., You, F. (2020). A Transformation-Proximal Bundle Algorithm for Multistage Adaptive Robust Optimization and Application to Constrained Robust Optimal Control. Automatica, 113, 108802.

• Ning, C., You, F. (2019). Data-Driven Adaptive Robust Unit Commitment under Wind Power Uncertainty: A Bayesian Nonparametric Approach. IEEE Transactions on Power Systems, 34, 2409-2418. (🏆 AIChE Sustainable Engineering Forum Student Paper Award)

• Ning, C., You, F. (2019). Optimization under Uncertainty in the Era of Big Data and Deep Learning: When Machine Learning Meets Mathematical Programming. Computers & Chemical Engineering, 125, 434-448. (Review Paper)

• Ning, C., You, F. (2019). Data-Driven Wasserstein Distributionally Robust Optimization for Biomass with Agricultural Waste-to-Energy Network Design under Uncertainty. Applied Energy, 255, 113857.

• Zhao, L., Ning, C., You, F. (2019). Operational Optimization of Industrial Steam Systems under Uncertainty Using Data-Driven Adaptive Robust Optimization. AIChE Journal, 65, e16500.

• Nicoletti, J., Ning, C., You, F. (2019). Incorporating Agricultural Waste-to-Energy Pathways into Biomass Product and Process Network through Data-Driven Nonlinear Adaptive Robust Optimization. Energy, 180, 556-571.

• Gao, J., Ning, C., You, F. (2019). Data-Driven Distributionally Robust Optimization for Shale Gas Supply Chain Design and Operations under Uncertainty. AIChE Journal, 3, 947-963.

• Ning, C., You, F. (2019). Data-Driven Adaptive Robust Optimization Framework for Unit Commitment under Renewable Energy Generation Uncertainty. American Control Conference (ACC), 4734-4739. （🏆 O. Hugo Schuck Best Paper Award）

• Ning, C., You, F. (2019). Chemical Process Scheduling under Disjunctive Uncertainty Using Data-Driven Multistage Adaptive Robust Optimization. American Control Conference (ACC), 2145-2150.

• Ning, C., You, F. (2019). A Transformation-Proximal Bundle Algorithm for Solving Multistage Adaptive Robust Optimization Problems. 57th IEEE Conference on Decision and Control (CDC), 2018, 2439-2444.

• Ning, C., You, F. (2018). Data-Driven Decision Making under Uncertainty Integrating Robust Optimization with Principal Component Analysis and Kernel Smoothing Methods. Computers & Chemical Engineering, 112, 190-210.

• Ning, C., You, F. (2018). Data-Driven Stochastic Robust Optimization: General Computational Framework and Algorithm Leveraging Machine Learning for Optimization under Uncertainty in the Big Data Era. Computers & Chemical Engineering, 111, 115-133.

• Ning, C., You, F. (2018). Adaptive Robust Optimization with Minimax Regret Criterion: Multiobjective Optimization Framework and Computational Algorithm for Planning and Scheduling under Uncertainty. Computers & Chemical Engineering, 108, 425-447.

• Ning, C., You, F. (2018). Data-Driven Adaptive Robust Optimization Framework Based on Principal Component Analysis. American Control Conference (ACC), 3020-3025.

• Ning, C., You, F. (2017). Data-Driven Adaptive Nested Robust Optimization: General Modeling Framework and Efficient Computational Algorithm for Decision Making under Uncertainty. AIChE Journal, 63, 3790-3817.

• Ning, C., You, F. (2017). A Data-Driven Multistage Adaptive Robust Optimization Framework for Planning and Scheduling under Uncertainty. AIChE Journal, 63, 4343-4369.

• Ning, C., You, F. (2017). Leveraging Big Data for Adaptive Robust Optimization of Scheduling under Uncertainty. American Control Conference (ACC), 3783-3788.

• Ning, C., You, F. (2016). Data-Driven Robust MILP Model for Scheduling of Multipurpose Batch Processes under Uncertainty. 55th IEEE Conference on Decision and Control (CDC), 2016, 6180-6185.

• Ning, C., Chen, M., Zhou, D. (2015) Sparse Contribution Plot for Fault Diagnosis of Multimodal Chemical Process. IFAC-PaperOnline, 48 (21), 619-626.

• Ning, C., Chen, M., Zhou, D. (2015). Fault Reconstruction for Multiple Failure Modes Based on Threshold Fault Subspace Extraction Algorithm. Journal of Shanghai Jiao Tong University, 2015, 49(6): 780-785.

• Ning, C., Chen, M., Zhou, D. (2014). Hidden Markov Model-Based Statistics Pattern Analysis for Multimode Process Monitoring: An Index-Switching Scheme. Industrial & Engineering Chemistry Research, 53, 11084-11095.