博文
【当期目录】IEEE/CAA JAS 第9卷 第3期
|
>热点主题
信息物理系统、深度学习、机器学习、大数据、最优控制、滑模控制、人机交互...
>全球科研机构
美国Michigan State University、University of Illinois Chicago；英国University of Lincoln；西班牙University of Seville；澳大利亚Swinburne University of Technology、Deakin University、James Cook University；中国科学院自动化研究所、清华大学、北京理工大学、哈尔滨工业大学、西安交通大学、华中科技大学...
Jun Zhang, Lei Pan, Qing-Long Han, Chao Chen, Sheng Wen and Yang Xiang, "Deep Learning Based Attack Detection for Cyber-Physical System Cybersecurity: A Survey," IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 377-391, Mar. 2022. ✪ Conduct an up-to-date review of detecting cyber attacks in CPSs using DL models and propose a six-step methodology to position and analyze the surveyed works. ✪ Provide an overview for the state-of-the-art solutions with preservation of technical details. ✪ Based on the methodology, we discuss the challenges and future research directions. Ligang Wu, Jianxing Liu, Sergio Vazquez and Sudip K. Mazumder, "Sliding Mode Control in Power Converters and Drives: A Review," IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 392-406, Mar. 2022. ✪ Briefs the fundamental theory and methodologies of SMC. ✪ The use of SMC for different types of power electronics systems are presented. ✪ Future challenges to adopt SMC as an industry solution to power converters are addressed. Mohamed Amine Ferrag, Lei Shu, Othmane Friha and Xing Yang, "Cyber Security Intrusion Detection for Agriculture 4.0: Machine Learning-Based Solutions, Datasets, and Future Directions," IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 407-436, Mar. 2022. ✪ Present the cyber security threats and evaluation metrics used in the performance evaluation of IDSs for Agriculture 4.0. ✪ Provide a comprehensive classification and in-depth analysis of machine learning and deep learning based IDSs for cyber security in Agriculture 4.0. ✪ Provide a detailed description of the current best practices, implementation frameworks, and public datasets used in the performance evaluation of IDSs for Agriculture 4.0. Zahra Marvi and Bahare Kiumarsi, "Barrier-Certified Learning-Enabled Safe Control Design for Systems Operating in Uncertain Environments," IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 437-449, Mar. 2022. ✪ The problem of safe control design for systems operating in uncertain shared environments is formulated as two sets of decoupled dynamics with a safety criterion defined as a function of both ego and external agent’s states to have a more inclusive scheme for safety-critical systems operating in cluttered environment. ✪ A novel learning-enabled ZCBF is proposed which is capable of safety guarantee during learning of unknown dynamics. ✪ Safety-aware model learning is proposed for rapid convergence of the approximated safe set to the exact one. Lujuan Dang, Badong Chen, Yulong Huang, Yonggang Zhang and Haiquan Zhao, "Cubature Kalman Filter Under Minimum Error Entropy With Fiducial Points for INS/GPS Integration," IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 450-465, Mar. 2022. ✪ The MEEF-CKF is developed by applying the minimum error entropy with fiducial points (MEEF) to CKF, where the MEEF can automatically locate the peak of the error probability density function (PDF) at zero and is beneficial for robustness enhancement. ✪ A novel optimization approach is presented for determining the free parameters of MEEF-CKF adaptively. ✪ The complexity of MEEF-CKF is analyzed in detail, which indicates an acceptable burden in comparison with traditional Kalman filters. In addition, a sufficient condition is provided for ensuring the convergence of the fixed-point iteration in MEEF-CKF. Majid Mazouchi, Subramanya Nageshrao and Hamidreza Modares, "Conflict-Aware Safe Reinforcement Learning: A Meta-Cognitive Learning Framework," IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 466-481, Mar. 2022. ✪ The proposed algorithm provides safety and performance guarantees across a variety of circumstances that the system might encounter. ✪ The bilevel learning control architecture is utilized. ✪ A higher meta-cognitive layer leverages a data-driven receding-horizon attentional controller to adapt the relative attention to different system’s safety and performance requirements. Zhiwei Hao, Xiaokui Yue, Haowei Wen and Chuang Liu, "Full-State-Constrained Non-Certainty-Equivalent Adaptive Control for Satellite Swarm Subject to Input Fault," IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 482-495, Mar. 2022. ✪ Develop a BLF-DSA controller to stabilize the uncertain satellite swarm system. ✪ Provide a non-CE adaptive scheme to overcome system uncertainties and input fault. ✪ Guarantee predefined full-state constraints for satellite swarm with input fault. Ruhul Amin Khalil, Nasir Saeed, Mohammad Inayatullah Babar, Tariqullah Jan and Sadia Din, "Bayesian Multidimensional Scaling for Location Awareness in Hybrid-Internet of Underwater Things," IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 496-509, Mar. 2022. ✪ Propose a hybrid BMDS based localization technique that can work on a fully hybrid IoUT network where the nodes can communicate using either optical, magnetic induction, and acoustic technologies. ✪ The proposed algorithm suggests that each sensor node attempts to search for the overall neighbourhood by utilizing any of the communication technology and estimate the range to the adjacent nodes. ✪ Some sensor nodes are not lying in the communication range of each other and can utilize the available connectiv- ity information and estimate the missing pairwise ranges. Bixiao Wu, Junpei Zhong and Chenguang Yang, "A Visual-Based Gesture Prediction Framework Applied in Social Robots," IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 510-519, Mar. 2022. ✪ A method for predicting gestures based on the LSTM is proposed. The data of gestures is collected by the Leap Motion. ✪ In order to reduce or eliminate the jitter or jump generated in the process of acquiring data by the Leap Motion, the Kalman filter is applied to solve this problem effectively. ✪ Propose a reliable feature extraction method, which extracts coordinate features, length features, angle features and angular velocity features, and combines these features to predict gestures. Lina Xia, Qing Li, Ruizhuo Song and Hamidreza Modares, "Optimal Synchronization Control of Heterogeneous Asymmetric Input-Constrained Unknown Nonlinear MASs via Reinforcement Learning," IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 520-532, Mar. 2022. ✪ A state space transformation method is presented to solve the optimal synchronization control problem for heterogeneous nonlinear MASs with asymmetric input constraints. ✪ An improved data-based RL algorithm is employed to learn the solution to the non-quadratic HJB equations without requiring system’s dynamics information. ✪ To implement this algorithm, the critic NN and the actor factor NN are established respectively to estimate the cost function and the control policy for agents, such that input constraint is encoded into the framework of the proposed algorithm. Hao Wu, Xin Luo, MengChu Zhou, Muhyaddin J. Rawa, Khaled Sedraoui and Aiiad Albeshri, "A PID-incorporated Latent Factorization of Tensors Approach to Dynamically Weighted Directed Network Analysis," IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 533-546, Mar. 2022. ✪ Proposes a PLFT model that performs latent feature analysis on an HDI tensor with high efficiency and accuracy. ✪ Presents detailed algorithm design and analysis for PLFT, which provides specific guidance for researchers to implement a PLFT model for DWDN analyses. ✪ Conducts empirical studies on two large-scale DWDNs from a real system to show PLFT’s impressively high efficiency and competitive link prediction accuracy. Kun Zhu, Chengpu Yu and Yiming Wan, "Recursive Least Squares Identification With Variable-Direction Forgetting via Oblique Projection Decomposition," IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 547-555, Mar. 2022. ✪ A VDF algorithm is proposed for identifying MO systems under non-persistent excitation. ✪ The VDF strategy relies on oblique projection decomposition of the information matrix. ✪ Boundedness of the information matrix is proved under non-persistent excitation. Xiaofei Zhang, Hongbin Ma, Wenchao Zuo and Man Luo, "Adaptive Control of Discrete-time Nonlinear Systems Using ITF-ORVFL," IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 556-563, Mar. 2022. ✪ A new application of random vector functional link networks in control algorithms. ✪ The stability analysis of the control systems based on random vector functional link networks. ✪ An online learning algorithm for training random vector functional link networks. WenJun Huang, PeiYun Zhang, YuTong Chen, MengChu Zhou, Yusuf Al-Turki and Abdullah Abusorrah, "QoS Prediction Model of Cloud Services Based on Deep Learning," IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 564-566, Mar. 2022. Junjie Wang, Qichao Zhang and Dongbin Zhao, "Highway Lane Change Decision-Making via Attention-Based Deep Reinforcement Learning," IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 567-569, Mar. 2022. Yadi Wang, Zefeng Zhang and Yinghao Lin, "Multi-Cluster Feature Selection Based on Isometric Mapping," IEEE/CAA J. Autom. Sinica, vol. 9, no. 3, pp. 570-572, Mar. 2022.
https://blog.sciencenet.cn/blog-3291369-1332038.html
上一篇：数据驱动的保证收敛速率最优输出调节
下一篇：分级特征反馈融合的深度图像超分辨率重建
