A journal of IEEE and CAA , publishes
high-quality papers in English on original
theoretical/experimental research
and development in all areas of automation
IEEE/CAA Journal of Automatica Sinica
| Citation: | T. Zhang and D. Yue, “Embodied-intelligence power industrial control systems: Architecture design, key scientific problems, and research recommendations,” IEEE/CAA J. Autom. Sinica, vol. 13, no. 2, pp. 239–242, Feb. 2026. doi: 10.1109/JAS.2026.125846
|
| [1] |
Y. Dong, X. Shan, Y. Yan, X. Leng, and Y. Wang, “Architecture, key technologies and applications of load dispatching in China power grid,” Journal of Modern Power Systems and Clean Energy, vol. 10, no. 2, pp. 316–327, 2022. doi: 10.35833/mpce.2021.000685
|
| [2] |
T. Zhang, S. Liu, W. Qiu, Z. Lin, L. Zhu, D. Zhao, M. Qian, and L. Yang, “KPI-based real-time situational awareness for power systems with a high proportion of renewable energy sources,” CSEE Journal of Power and Energy Systems, vol. 8, no. 4, pp. 1060–1073, 2022. doi: 10.17775/cseejpes.2020.01530
|
| [3] |
Y. Shu, Y. Tang, Z. Zhang, F. Zhang, W. Zhong, H. Shi, L. Yang, M. Kong, Z. Gu, and Y. Yu, “Pathway for new-type power system in China,” CSEE Journal of Power and Energy Systems, vol. 11, no. 6, pp. 2684–2695, 2025. doi: 10.17775/cseejpes.2025.05700
|
| [4] |
S. Zhang and J. J. Q. Yu, “Bayesian deep learning for dynamic power system state prediction considering renewable energy uncertainty,” Journal of Modern Power Systems and Clean Energy, vol. 10, no. 4, pp. 913–922, 2022. doi: 10.35833/mpce.2020.000939
|
| [5] |
T. Shen, J. Sun, S. Kong, Y. Wang, J. Li, X. Li, and F.-Y. Wang, “The journey/DAO/TAO of embodied intelligence: From large models to foundation intelligence and parallel intelligence,” IEEE/CAA Journal of Automatica Sinica, vol. 11, no. 6, pp. 1313–1316, 2024. doi: 10.1109/JAS.2024.124407
|
| [6] |
J. Ding, Y. Zhang, Y. Shang, Y. Zhang, Z. Zong, J. Feng, Y. Yuan, H. Su, N. Li, N. Sukiennik, et al., “Understanding world or predicting future? A comprehensive survey of world models,” ACM Computing Surveys, vol. 58, no. 3, pp. 1–38, 2025. doi: 10.1145/3746449
|
| [7] |
R. Sapkota, Y. Cao, K. I. Roumeliotis, and M. Karkee, “Vision-language-action (VLA) models: Concepts, progress, applications and challenges,” arXiv preprint arXiv: 2505.04769, 2025.
|
| [8] |
O. Dogru, J. Xie, O. Prakash, R. Chiplunkar, J. Soesanto, H. Chen, K. Velswamy, F. Ibrahim, and B. Huang, “Reinforcement learning in process industries: Review and perspective,” IEEE/CAA Journal of Automatica Sinica, vol. 11, no. 2, pp. 283–300, 2024. doi: 10.1109/JAS.2024.124227
|
| [9] |
M. Gonzalez, “Challenges of variable energy resource integration and power system security: Lessons from the 2025 Iberian system blackout,” Transactions on Energy Systems and Engineering Applications, vol. 6, no. 1, pp. 1–6, 2025. doi: 10.32397/tesea.vol6.n1.911
|
Figures(1)
DownLoad: