博文
【当期目录】IEEE/CAA JAS 第10卷 第3期
|
主题
非线性仿射控制系统，机器学习，机器人，非线性系统，自适应控制，优化，多智能体，预测控制，人工智能，计算机视觉，卷积神经网络，最优控制...
全球科研机构
新加坡Nanyang Technological University；澳大利亚University of Technology Sydney、University of New South Wales；加拿大University of Waterloo；韩国Ulsan National Institute of Science and Technology；中科院自动化所、北京理工大学、上海交通大学、哈尔滨工业大学、中国石油大学（北京）、北京科技大学、北京交通大学、华南理工大学、东南大学、南京大学...
F.-Y. Wang, Q. Miao, X. Li, X. Wang, and Y. Lin, "What does ChatGPT say: The DAO from algorithmic intelligence to linguistic intelligence, " IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 575–579, Mar. 2023. C. H. Zhang and S. Liu, “Meta-energy: When integrated energy internet meets metaverse,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 580–583, Mar. 2023. B. Q. Li, S. P. Wen, Z. Yan, G. H. Wen, and T. W. Huang, “A survey on the control Lyapunov function and control barrier function for nonlinear-affine control systems,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 584–602, Mar. 2023. > Provides a brief overview on the control problems of general nonlinear-affine control systems with the help of CLF and CBF. > Combines the CLF and CBF with the QP optimization framework to obtain the optimal control protocol for general nonlinear-affine control systems. > Reveals the contributions of CLF-CBF-based QP on the performances of nonlinear-affine control systems and reviews the recent theoretical progress and novel applications. Q. H. Miao, Y. S. Lv, M. Huang, X. Wang, and F.-Y. Wang, “Parallel learning: Overview and perspective for computational learning across Syn2Real and Sim2Real,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 603–631, Mar. 2023. > An extended Parallel Learning framework covering main machine learning tasks including computer vision, natural lan- guage processing, robotics and autonomous driving. > A systematical survey of the existing methods via virtual- to-real paradigm from the viewpoints of parallel learning. > A multi-dimensional and multi-level taxonomy of virtual- to-real methods. X. Y. Liu, T. Ma, Z. X. Tang, X. H. Qin, H. B. Zhou, and X. M. Shen, “UltraStar: A lightweight simulator of ultra-dense LEO satellite constellation networking for 6G,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 632–645, Mar. 2023. > A systematic and extensible simulation framework for mega-constellations is proposed. > Modules of topology, network, discrete event and visualization are newly designed. > First trial to simulate such constellations of more than 10,000 satellites. V. P. Tran, M. A. Garratt, K. Kasmarik, and S. G. Anavatti, “Dynamic frontier-led swarming: Multi-robot repeated coverage in dynamic environments,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 646–661, Mar. 2023. > Present the novel multi-robot repeated area coverage and obstacle avoidance methods. > Propose a flocking model to maintain a close-knit formation. > Construct an evaluation of our method in different settings. J. Q. Liang, X. H. Bu, L. Z. Cui, and Z. S. Hou, “Event-triggered asymmetric bipartite consensus tracking for nonlinear multi-agent systems based on model-free adaptive control,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 662–672, Mar. 2023. > An asymmetric bipartite consensus control for the multi-agent systems is studied. > An event-triggered MFAC data-driven protocol is proposed for the completely unknown nonlinear multi-agent systems in an asynchronous triggering way. > An asymmetric coefficient related sufficient condition and a requirement on signed digraph that out-degree not lager than in-degree are derived for the system convergence. L. Ma, Y.-L. Wang, and Q.-L. Han, “Cooperative target tracking of multiple autonomous surface vehicles under switching interaction topologies,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 673–684, Mar. 2023. > For the target to be tracked, only its position can be measured/received by some of the ASVs, and its velocity is unavailable to all the ASVs, a distributed extended state observer is designed to integrally estimate unknown target dynamics and neighboring ASVs' dynamics. > A novel kinematic controller is designed, which takes full advantage of known information and avoids the approximation of some virtual control vectors. > A disturbance observer is presented to estimate unknown time-varying environmental disturbance. J. Hou, X. Zeng, G. Wang, J. Sun, and J. Chen, “Distributed momentum-based Frank-Wolfe algorithm for stochastic optimization,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 685–699, Mar. 2023. > A distributed stochastic Frank-Wolfe algorithm is proposed for stochastic optimization problems by judiciously combining Nesterov’s momentum and gradient tracking techniques. > Convergence rate results of the proposed algorithm for convex and nonconvex problems are established. > Efficacy of the algorithm is demonstrated by numerical simulations against a number of competing alternatives. J. Wang, S. Y. Li, and Y. Y. Zou, “Connectivity-maintaining consensus of multi-agent systems with communication management based on predictive control strategy,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 700–710, Mar. 2023. > A scheme including a communication management strategy and a predictive control based strategy is designed for the multi-agent systems that the connectivity-maintaining consensus can be achieved and the communication energy can be saved. > Proposed novel communication management strategy is not coupled with controller but only impose a constraint for controller. > A predictive control based strategy is designed with this novel communication management strategy, and compared to the related literature, the scheme in this paper can save more communication energy. Y. Liu, B. Jiang, and J. M. Xu, “Axial assembled correspondence network for few-shot semantic segmentation,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 711–721, Mar. 2023. > Develop a novel 4d kernel (AA-Conv4d). It conducts an appropriate weight-sparsification while keeping sufficient communications between the support and the query subspaces. >Propose a simple but effective preprocessing module to modify the statistical distribution of the semantic correspondences, which can effectively improve segmentation performance. >By mixing pyramid correspondences with a learnable concatenation operation, our FM helps adaptively refine the squeezed correspondences for query segmentation. D. Yu, M. Y. Zhang, M. T. Li, F. S. Zha, J. G. Zhang, L. N. Sun, and K. Q. Huang, “Squeezing more past knowledge for online class-incremental continual learning,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 722–736, Mar. 2023. > Propose a hierarchical replay-based method for online class-incremental CL. > Besides the previous raw samples, we store the corresponding logits and features and construct multi-level constraints to imitate the predictions of the past model. > Replaying the same number of samples, our method achieves state-of-the-art performance. C. J. Li and X. F. Zong, “Group hybrid coordination control of multi-agent systems with time-delays and additive noises,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 737–748, Mar. 2023. > A new kind of group coordination control problem——group hybrid coordination control is investigated. > Using the semi-decoupled skill and some estimation methods, this work provides a new analysis idea to investigate the group hybrid coordination control problem under time-delays and additive noises. conditions are obtained for this problem. > Influence mechanism of the communication impact between the two subgroups on group hybrid coordination control problem of MASs with both time-delays and additive noises is revealed. H. Wang, T. F. Zhang, X. Y. Zhang, and Q. Li, “Observer-based path tracking controller design for autonomous ground vehicles with input saturation,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 749–761, Mar. 2023. > Nonlinear vehicle model is reformulated as a polytopic LPV system with input saturation. > Frequency domain characteristics of the derivative of desired heading angles are analyzed. > An observer-based finite frequency path tracking controller is designed. M. Ghorbani, M. Tavakoli-Kakhki, A. Tepljakov, and E. Petlenkov, “Robust stability analysis of smith predictor based interval fractional-order control systems: A case study in level control process,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 762–780, Mar. 2023. > Presenting a finite frequency range for verifying the robust stability of a Smith predictor-based control system. > Obtaining necessary and sufficient conditions for robust stability analysis of a designed Smith predictor-based control system. > Introducing a robust stability testing function to investigate the robust stability of Smith predictor based fractional-order control system. G. Y. Zhu, X. L. Li, R. R. Sun, Y. Y. Yang, and P. Zhang, “Policy iteration for optimal control of discrete-time time-varying nonlinear systems,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 781–791, Mar. 2023. > A novel iterative adaptive dynamic programming method is presented for the infinite horizon optimal control problem of discrete time-varying nonlinear systems. > Properties of the discrete-time time-varying policy iteration method, including monotonicity, convergence and optimality, are analyzed in detail. > Critic neural network and actor neural network are introduced to implement the presented method. Y. C. Li, W. B. Yu, and X. P. Guan, “Current-aided multiple-AUV cooperative localization and target tracking in anchor-free environments,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 792–806, Mar. 2023. > A distributed current-aided belief propagation message-passing scheme is designed for multi-AUV cooperative localization and target tracking. > Current-aided cooperative localization alleviates the impact of the accumulated errors in inertial measurements and improves localization accuracy in the absence of anchors. > Improved prediction accuracy for the noncooperative target tracking is achieved with the help of current maps and is with good adaptability to different target motions and map qualities. Z. J. Hu, R. Su, K. Zhang, Z. Y. Xu, and R. J. Ma, “Resilient event-triggered model predictive control for adaptive cruise control under sensor attacks,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 807–809, Mar. 2023. X. Gu, Y. L. Shang, Y. Z. Kang, J. L. Li, Z. H. Mao, and C. H. Zhang, “An early minor-fault diagnosis method for lithium-ion battery packs based on unsupervised learning,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 810–812, Mar. 2023. E. T. Pan, Y. Ma, X. G. Mei, J. Huang, F. Fan, and J. Y. Ma, “D2Net: Deep denoising network in frequency domain for hyperspectral image,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 813–815, Mar. 2023. T. Q. Yu, Y.-J. Liu, and L. Liu, “Adaptive neural control for nonlinear MIMO function constraint systems,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 816–818, Mar. 2023. K. Xia, S.-M. Lee, W. Chung, Y. Zou, and H. Son, “Moving target landing of a quadrotor using robust optimal guaranteed cost control,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 819–821, Mar. 2023. J. Y. Guo, Y. L. Yue, B. Y. Song, and Z. Y. Zhao, “Finite-horizon l2–l∞ state estimation for networked systems under mixed protocols,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 822–824, Mar. 2023. X. Liang, W. W. Yan, Y. S. Fu, and H. H. Shao, “Process monitoring based on temporal feature agglomeration and enhancement,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 825–827, Mar. 2023. J. Y. He, J. B. Wen, S. Xiao, and J. C. Yang, “Multi-AUV inspection for process monitoring of underwater oil transportation,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 828–830, Mar. 2023.
https://blog.sciencenet.cn/blog-3291369-1381177.html
上一篇：《自动化学报》2023年49卷2期目录分享
下一篇：无人机反应式扰动流体路径规划
