Research outputs
2025
Nash equilibrium seeking in non-cooperative heterogeneous multi-robot systems via output regulation
Dong, Y., Li, Z., Ehsan, S., Ding, Z., & Huang, X. (2025). Nash equilibrium seeking in non-cooperative heterogeneous multi-robot systems via output regulation. Neurocomputing, 619, 129179. doi:10.1016/j.neucom.2024.129179
Hierarchical Testing With Rabbit Optimization for Industrial Cyber-Physical Systems
Hu, J., Tang, Z., Jin, X., Zhang, B., Dong, Y., & Huang, X. (2025). Hierarchical Testing With Rabbit Optimization for Industrial Cyber-Physical Systems. IEEE Transactions on Industrial Cyber-Physical Systems, 3, 472-484. doi:10.1109/ticps.2025.3586988
2024
Reachability Verification Based Reliability Assessment for Deep Reinforcement Learning Controlled Robotics and Autonomous Systems
Dong, Y., Zhao, X., Wang, S., & Huang, X. (2024). Reachability Verification Based Reliability Assessment for Deep Reinforcement Learning Controlled Robotics and Autonomous Systems. IEEE Robotics and Automation Letters, 1-8. doi:10.1109/lra.2024.3364471
Privacy-Preserving Distributed Learning for Residential Short-Term Load Forecasting
Dong, Y., Wang, Y., Gama, M., Mustafa, M. A., Deconinck, G., & Huang, X. (2024). Privacy-Preserving Distributed Learning for Residential Short-Term Load Forecasting. IEEE Internet of Things Journal, 1. doi:10.1109/jiot.2024.3362587
2023
Short-term Load Forecasting with Distributed Long Short-Term Memory
Dong, Y., Chen, Y., Zhao, X., & Huang, X. (2023). Short-term Load Forecasting with Distributed Long Short-Term Memory. In 2023 IEEE POWER & ENERGY SOCIETY INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE, ISGT. doi:10.1109/ISGT51731.2023.10066368
Decentralised and Cooperative Control of Multi-Robot Systems through Distributed Optimisation
Dong, Y., Li, Z., Zhao, X., Ding, Z., & Huang, X. (2023). Decentralised and Cooperative Control of Multi-Robot Systems through Distributed Optimisation. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems Aamas Vol. 2023-May (pp. 1421-1429).
2022
Dependability Analysis of Deep Reinforcement Learning based Robotics and Autonomous Systems through Probabilistic Model Checking
Dong, Y., Zhao, X., & Huang, X. (2022). Dependability Analysis of Deep Reinforcement Learning based Robotics and Autonomous Systems through Probabilistic Model Checking. In 2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) (pp. 5171-5178). doi:10.1109/IROS47612.2022.9981794
Short-term Load Forecasting with Distributed Long Short-Term Memory
Dong, Y., Chen, Y., Zhao, X., & Huang, X. (2022). Short-term Load Forecasting with Distributed Long Short-Term Memory. Retrieved from http://arxiv.org/abs/2208.01147v2
Dependability Analysis of Deep Reinforcement Learning based Robotics and Autonomous Systems through Probabilistic Model Checking
Dong, Y., Zhao, X., & Huang, X. (2021). Dependability Analysis of Deep Reinforcement Learning based Robotics and Autonomous Systems through Probabilistic Model Checking. Retrieved from http://dx.doi.org/10.1109/IROS47612.2022.9981794
EnnCore: End-to-End Conceptual Guarding of Neural Architectures
Manino, E., Carvalho, D., Dong, Y., Rozanova, J., Song, X., Mustafa, M. A., . . . Cordeiro, L. (2022). EnnCore: End-to-End Conceptual Guarding of Neural Architectures. In Ceur Workshop Proceedings Vol. 3087.
2021
Reliability Assessment and Safety Arguments for Machine Learning Components in System Assurance
Dong, Y., Huang, W., Bharti, V., Cox, V., Banks, A., Wang, S., . . . Huang, X. (2023). Reliability Assessment and Safety Arguments for Machine Learning Components in System Assurance. ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS, 22(3). doi:10.1145/3570918
Short term load forecasting with markovian switching distributed deep belief networks
Dong, Y., Dong, Z., Zhao, T., Li, Z., & Ding, Z. (2021). Short term load forecasting with markovian switching distributed deep belief networks. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 130. doi:10.1016/j.ijepes.2021.106942
A Strategic Day-ahead bidding strategy and operation for battery energy storage system by reinforcement learning
Dong, Y., Dong, Z., Zhao, T., & Ding, Z. (2021). A Strategic Day-ahead bidding strategy and operation for battery energy storage system by reinforcement learning. ELECTRIC POWER SYSTEMS RESEARCH, 196. doi:10.1016/j.epsr.2021.107229
Detecting Operational Adversarial Examples for Reliable Deep Learning
Zhao, X., Huang, W., Schewe, S., Dong, Y., & Huang, X. (2021). Detecting Operational Adversarial Examples for Reliable Deep Learning. In 51ST ANNUAL IEEE/IFIP INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS - SUPPLEMENTAL VOL (DSN 2021) (pp. 5-6). doi:10.1109/DSN-S52858.2021.00013
Fully-Distributed Deloading Operation of DFIG-Based Wind Farm for Load Sharing
Dong, Z., Li, Z., Dong, Y., Jiang, S., & Ding, Z. (2021). Fully-Distributed Deloading Operation of DFIG-Based Wind Farm for Load Sharing. IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 12(1), 430-440. doi:10.1109/TSTE.2020.3002690
2020
An Optimal Day-ahead Bidding Strategy and Operation for Battery Energy Storage System by Reinforcement Learning
Dong, Y., Zhao, T., & Ding, Z. (2020). An Optimal Day-ahead Bidding Strategy and Operation for Battery Energy Storage System by Reinforcement Learning. In IFAC PAPERSONLINE Vol. 53 (pp. 13190-13195). doi:10.1016/j.ifacol.2020.12.144
2019
Demand-side management using a distributed initialisation-free optimisation in a smart grid
Dong, Y., Zhao, T., & Ding, Z. (2019). Demand-side management using a distributed initialisation-free optimisation in a smart grid. IET RENEWABLE POWER GENERATION, 13(9), 1533-1543. doi:10.1049/iet-rpg.2018.5858