【CAA期刊】IEEE/CAA JAS第12卷第9期

Y. Zhu, J. Che, F. Wu, X. Chen, W. Zheng, and D. Zhou, “Stability, control and fault diagnosis of switched linear parameter varying systems: A survey,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 9, pp. 1745–1761, Sept. 2025. 

Doi: 10.1109/JAS.2025.125282

K. Bojappa and J. Lee, “Review on particle swarm optimization: application toward autonomous dynamical systems,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 9, pp. 1762–1775, Sept. 2025. 

Doi: 10.1109/JAS.2024.125028 

J. Chen, W. Gui, N. Chen, B. Luo, B. Li, Z. Luo, and C. Yang, “Data-driven time-delay optimal control method for roller kiln temperature field,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 9, pp. 1776–1787, Sept. 2025. 

Doi: 10.1109/JAS.2025.125309

>Considering high complexity of precise modeling, a data-driven time-delay optimal control method for temperature field of roller kiln is proposed based on a large amount of process data. 

R. Chen, D. Zhou, and L. Sheng, “Adaptive fault-tolerant control for unknown affine nonlinear systems based on self-organizing RBF neural network,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 9, pp. 1788–1800, Sept. 2025. 

Doi: 10.1109/JAS.2025.125441

>This article presents an adaptive fault-tolerant tracking control strategy for unknown affine nonlinear systems subject to actuator faults and external disturbances.

R. Wang, Z. Hu, J. Yu, and J. Cheng, “Modelling diverse interactions and multimodality for pedestrian trajectory prediction,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 9, pp. 1801–1813, Sept. 2025. 

Doi: 10.1109/JAS.2025.125363

>We propose to devise a hand-designed graph convolution and spatial cross attention to dynamically capture the diverse spatial interactions between pedestrians.

R. Chai, T. Liu, S. He, K. Chen, Y. Xia, H.-S. Shin, and A. Tsourdos, “Adaptive dual-loop disturbance observer-based robust model predictive tracking control for autonomous hypersonic vehicles,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 9, pp. 1814–1829, Sept. 2025. 

Doi: 10.1109/JAS.2025.125291

>This paper designed a nonlinear robust model predictive control (RMPC) scheme, which can produce near-optimal tracking commands. 

X. Ban, J. Liang, K. Qiao, K. Yu, Y. Wang, J. Peng, and B. Qu, “A decision variables classification-based evolutionary algorithm for constrained multi-objective optimization problems,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 9, pp. 1830–1849, Sept. 2025. 

Doi: 10.1109/JAS.2025.125276

>This paper proposes a decision variables classification approach, according to the relationship between decision variables and constraints, variables are divided into constraint-related (CR) variables and constraint-independent (CI) variables. 

S. Yu, Y. Qiao, F. Yang, W. Zhao, and J. Bo, “Dynamic evolutionary game-based staking pool selection modeling and decentralization enhancement for blockchain system,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 9, pp. 1850–1865, Sept. 2025.

Doi: 10.1109/JAS.2025.125447 

>This study introduces an incentive-aligned mechanism named decentralized proof-of-stake (DePoS), wherein the second-largest stakeholder is chosen as the final validator with a higher probability.

G. Cheng, B. Qiu, J. Guo, and Y. Han, “A robust direct-discretized RNN for time-dependent optimization constrained by nonlinear equalities and its applications,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 9, pp. 1866–1877, Sept. 2025. 

Doi: 10.1109/JAS.2025.125627 

>To handle these issues, a robust direct-discretized RNN (RDD-RNN) model is proposed to efficiently realize time-dependent optimization constrained by nonlinear equalities (TDOCNE) in the presence of various time-dependent noises.

J. Deng, L. Zhang, W. Xue, Q. Bao, and Y. Mao, “Active compression on unknown disturbance and uncertainty via extended state observer,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 9, pp. 1878–1892, Sept. 2025. 

Doi: 10.1109/JAS.2025.125342

>To modify the disturbance estimation characteristics encountered by the observer, the active compression extended state observer (ACESO) is proposed in this study. 

J. Li, Q. Yu, G. Li, and Y. He, “The application of RVM in GNSS anti-spoofing field based on the hybrid kernel function,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 9, pp. 1893–1907, Sept. 2025. 

Doi: 10.1109/JAS.2025.125522 

>In this study, a GNSS spoofing jamming detection method based on hybrid kernel relevance vector machine (RVM) is proposed.

C. Li, X. Zhao, W. Xing, N. Xu, and N. Zhao, “Model-based decentralized dynamic periodic event-triggered control for nonlinear systems subject to packet losses,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 9, pp. 1908–1919, Sept. 2025. 

Doi: 10.1109/JAS.2025.125459

>This paper studies the problem of designing a model-based decentralized dynamic periodic event-triggering mechanism (DDPETM) for networked control systems (NCSs) subject to packet losses and external disturbances.

C. Fei, Y. Li, X. Huang, G. Zhang, and R. Lu, “Unsupervised dynamic discrete structure learning: A geometric evolution method,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 9, pp. 1920–1937, Sept. 2025. 

Doi: 10.1109/JAS.2025.125165

>This paper proposes a novel dynamic geometric structure learning model (DGSL) to explore the true latent nonlinear geometric structure. 

M.-F. Ge, Y.-F. Li, C.-B. Wu, Z.-W. Liu, Y. Jia, and S.-S. Liu, “Hierarchical event-triggered predictive control for cross-domain unmanned systems with mixed constraints,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 9, pp. 1938–1940, Sept. 2025. 

Doi: 10.1109/JAS.2024.124797

H. Zhu, J. Lu, Y. Lou, and X. Yang, “Distributed saturated impulsive quasi-consensus for leader-follower multi-agent systems: An open topology framework,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 9, pp. 1941–1943, Sept. 2025. 

Doi: 10.1109/JAS.2024.124743

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