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❁主题 轨迹规划、最优控制、动态系统、电力系统、优化、滑模控制、Q-Learning... ❁全球科研机构 美国New Jersey Institute of Technology;澳大利亚Swinburne University of Technology;墨西哥Autonomous University of Nuevo Leon;中科院自动化所、同济大学、香港城市大学(中国香港)、武汉大学、大连海事大学、南京理工大学... Fei-Yue Wang, "The DAO to MetaControl for MetaSystems in Metaverses: The System of Parallel Control Systems for Knowledge Automation and Control Intelligence in CPSS," IEEE/CAA J. Autom. Sinica, vol. 9, no. 11, pp. 1899-1908, Nov. 2022. doi: 10.1109/JAS.2022.106022 ........................................................................................................................................................... J. S. Wang, J. Wang, and Q.-L. Han, “Receding-horizon trajectory planning for under-actuated autonomous vehicles based on collaborative neurodynamic optimization,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 11, pp. 1909–1923, Nov. 2022. doi: 10.1109/JAS.2022.105524 > Receding-horizon trajectory planning of under-actuated vehicles is formulated as a sequential optimization problem with kinetic, kinematic, collision-avoidance constraints. > Conditions are derived for ensuring the feasibility of the sequential optimization problem. > Conditions are derived for the global convergence of the neurodynamics-driven trajectory planning method. ........................................................................................................................................................... C. Trapiello and V. Puig, “A zonotopic-based watermarking design to detect replay attacks,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 11, pp. 1924–1938, Nov. 2022. doi: 10.1109/JAS.2022.105944 > Proposal of a novel zonotope-based framework for analyzing replay attacks affecting remotely controlled systems. > Derivation of optimal expressions regarding the attack detection under zonotope-bounded uncertainties that are analogous to the ones obtained under Gaussian uncertainties. > Design of a novel guaranteed replay attack detection method that self-triggers the detection every time the sensor measurements are being replayed. ........................................................................................................................................................... Z. R. Zhu, Y. Chai, Z. M. Yang, and C. H. Huang, “Exponential-alpha safety criteria of a class of dynamic systems with barrier functions,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 11, pp. 1939–1951, Nov. 2022. doi: 10.1109/JAS.2020.1003408 > Proposed a novel safety criterion called Exponential-alpha safety criterion, where the alpha belongs to positive real number field. > Proposed a new control barrier function and then designed a safety controller for a classic kind of dynamic control systems. > Proposed Positive Multi-hypersphere Method and Reverse Multi-hypersphere Method. ........................................................................................................................................................... M. J. Cui, L. Li, M. C. Zhou, J. K. Li, A. Abusorrah, and K. Sedraoui, “A bi-population cooperative optimization algorithm assisted by an autoencoder for medium-scale expensive problems,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 11, pp. 1952–1966, Nov. 2022. doi: 10.1109/JAS.2022.105425 > Presents an autoencoder-embedded evolutionary optimization framework to advance the field of medium-scale expensive optimization. > To generate promising offspring for MEPs, we take advantage of autoencoders for dimension reduction, which is embedded in the framework of traditional EAs. > A bi-population cooperative evolution strategy is proposed to balance its exploration and exploitation, where one is evolved with help of an autoencoder and the other with a regular evolution. ........................................................................................................................................................... Y. B. Gao, “Adaptive generalized eigenvector estimating algorithm for hermitian matrix pencil,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 11, pp. 1967–1979, Nov. 2022. doi: 10.1109/JAS.2021.1003955 > To estimate the first generalized eigenvector, a novel algorithm is proposed when the matrix pencil is explicitly provided. > To prove the convergence result of the proposed algorithm, the fixed stability of the proposed algorithm is analyzed by the Lyapunov function approach. > Convergence analysis is accomplished by the DDT method and some convergence conditions are also obtained. ........................................................................................................................................................... Z. W. Deng and C. Xu, “Frequency regulation of power systems with a wind farm by sliding-mode-based design,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 11, pp. 1980–1989, Nov. 2022. doi: 10.1109/JAS.2022.105407 > A LFC method based on the derivative and integral terminal sliding mode technology is investigated for multi-area interconnected power systems integrated with wind power. > Considering the flexibility of wind power regulation, wind generators are also applied to provide frequency support by adopting a wind power system model based on the mechanical dynamics of VSWTs. > Numerical simulations are carried out, which indicated that the proposed LFC method has the advantages of fast convergence and small oscillation. ........................................................................................................................................................... L. Y. Yang, C. Lv, X. Wang, J. Qiao, W. P. Ding, J. Zhang, and F.-Y. Wang, “Collective entity alignment for knowledge fusion of power grid dispatching knowledge graphs,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 11, pp. 1990–2004, Nov. 2022. doi: 10.1109/JAS.2022.105947 > Collective entity alignment model for the knowledge fusion of multiple power grid dispatching knowledge graphs is proposed. > Novel knowledge graph attention network is proposed to learn the structural relatedness of entities and relations explicitly. > Structural, attribute, and relational similarities between entities are adaptively integrated to obtain the synthesized similarities. ........................................................................................................................................................... L. J. Yue and H. M. Fan, “Dynamic scheduling and path planning of automated guided vehicles in automatic container terminal,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 11, pp. 2005–2019, Nov. 2022. doi: 10.1109/JAS.2022.105950 > AGV scheduling and path planning models are established to minimize costs. > Uncertain factor of path conflicts and failed path nodes are considered. > Rule-based heuristic algorithm composed of five principles is proposed. ........................................................................................................................................................... A. Garza-Alonso, M. Basin, and P. C. Rodriguez-Ramirez, “Predefined-time backstepping stabilization of autonomous nonlinear systems,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 11, pp. 2020–2022, Nov. 2022. doi: 10.1109/JAS.2022.105953 ........................................................................................................................................................... G. Cheng, Z. F. Shao, J. M. Wang, X. Huang, and C. Y. Dang, “Dual-branch multi-level feature aggregation network for pansharpening,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 11, pp. 2023–2026, Nov. 2022. doi: 10.1109/JAS.2022.105956 ........................................................................................................................................................... S. P. Wang, X. C. Lin, Z. H. Fang, S. D. Du, and G. B. Xiao, “Contrastive consensus graph learning for multi-view clustering,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 11, pp. 2027–2030, Nov. 2022. doi: 10.1109/JAS.2022.105959 ........................................................................................................................................................... B. Liu, R. Y. Song, Y. J. Xiang, J. B. Du, W. J. Ruan, and J. H. Hu, “Self-supervised entity alignment based on multi-modal contrastive learning,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 11, pp. 2031–2033, Nov. 2022. doi: 10.1109/JAS.2022.105962 ........................................................................................................................................................... M. Liu and M. S. Shang, “On RNN-based k-WTA models with time-dependent inputs,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 11, pp. 2034–2036, Nov. 2022. doi: 10.1109/JAS.2022.105932 ........................................................................................................................................................... H. L. Tan, B. Shen, Q. Li, and W. Qian, “Recursive filtering for nonlinear systems with self-interferences over full-duplex relay networks,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 11, pp. 2037–2040, Nov. 2022. doi: 10.1109/JAS.2022.105965
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