Ieee-Caa Journal of Automatica Sinica最新文献_第2页

A New Parameter Estimation Methodology Using Steady State Yaw Rate Measurements for Lateral Vehicle Dynamics 基于稳态横摆角速度测量的车辆横向动力学参数估计新方法

IF 18.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-09-01 Epub Date: 2026-10-01 DOI: 10.1109/JAS.2025.125366

Zhihong Man;Mingcong Deng;Zenghui Wang;Qing-Long Han

{"title":"A New Parameter Estimation Methodology Using Steady State Yaw Rate Measurements for Lateral Vehicle Dynamics","authors":"Zhihong Man;Mingcong Deng;Zenghui Wang;Qing-Long Han","doi":"10.1109/JAS.2025.125366","DOIUrl":"https://doi.org/10.1109/JAS.2025.125366","url":null,"abstract":"In this paper, the lateral dynamics of road vehicles (LDRV) is further studied from the viewpoint of vehicle informatics. It is seen that LDRV is first decoupled and the vehicle slip angle is proved to be observable from the yaw rate measurements. A new methodology of parameter estimation using steady-state yaw rate measurements (PESYRM) is then developed to accurately estimate the parameters of LDRV. The important characteristics of PESYRM comprise four parts: 1) The steering angle input to LDRV is chosen as the linear combination of sinusoids; 2) Only the steady state information of yaw rate in any fundamental period is required to accurately estimate the unknown parameters of LDRV; 3) Unlike many existing parameter estimation methods, the time consuming computing of the inverse of high-dimensional data matrix is avoided by making full use of the orthogonal properties of trigonometric base functions; 4) All of system information of LDRV is embedded in the measurements of the steady state yaw rate in any fundamental period. A simulation example is carried out to show the advantages and effectiveness of the new research findings for LDRV.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"13 9","pages":"2003-2018"},"PeriodicalIF":18.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149133647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reinforcement Learning-Based Predefined-Time Optimal Bipartite Consensus of High-Order Multiagent Systems 基于强化学习的高阶多智能体系统预定义时间最优二部一致性

IF 18.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-09-01 Epub Date: 2026-10-01 DOI: 10.1109/JAS.2025.125675

Lu Fan;Xiaoyang Liu;Wenwu Yu

引用次数: 0

Damping-Enhanced Zero-Effort-Miss Guidance for 3D Engagement: Strengthened Parallel Approach with Maneuvering Target Robustness 三维交战的阻尼增强零努力脱靶制导：具有机动目标鲁棒性的强化并行方法

IF 18.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-09-01 Epub Date: 2026-10-01 DOI: 10.1109/JAS.2025.125855

Wushuai Cui;Yuan Yuan

{"title":"Damping-Enhanced Zero-Effort-Miss Guidance for 3D Engagement: Strengthened Parallel Approach with Maneuvering Target Robustness","authors":"Wushuai Cui;Yuan Yuan","doi":"10.1109/JAS.2025.125855","DOIUrl":"https://doi.org/10.1109/JAS.2025.125855","url":null,"abstract":"Dear Editor, This letter proposes a novel three-dimensional (3D) guidance law based on the zero-effort-miss (ZEM) concept enhanced with a damping term. The key concept involved in the approach is the introduction of a damping term into the guidance law which effectively increases the degrees of freedom and strengthens the parallel approach characteristic. Based on this concept, two distinct formulations of the ZEM-based guidance law are derived, that is, the damping-enhanced ZEM (ZEM_DAMP) guidance law and the proportional navigation (PN_DAMP) guidance law. Especially, the PN_DAMP guidance law without knowing the acceleration information of the target is demonstrated to have superior performance compared with the augmented proportional navigation (APN) guidance law. The superiority of the proposed ZEM-based guidance law with the damping term is validated rigorously with the introduction of robustness against target maneuvers, ZEM error dynamics, and parallel approach characteristics. Finally, extensive numerical simulations validate that the inclusion of a damping term significantly improves the effectiveness of the guidance law.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"13 9","pages":"2184-2186"},"PeriodicalIF":18.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11716143","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149133653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Resilient Distributed Optimization with Trust Opinion Dynamics for Cyber-Physical Systems Over Directed Graphs 有向图上网络物理系统的信任意见动态弹性分布式优化

IF 18.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-09-01 Epub Date: 2026-09-29 DOI: 10.1109/JAS.2025.125657

Yifan Wang;Chengze Zhang;Xianghui Cao

引用次数: 0

Optimal Control of Nonlinear Systems via Predefined-Time Convergent Reinforcement Learning 基于预定义时间收敛强化学习的非线性系统最优控制

IF 18.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-09-01 Epub Date: 2026-09-29 DOI: 10.1109/JAS.2025.125699

Cong Zhang;Feng Xiao;Xiaodan Zhang;Bo Wei;Pin Liu

引用次数: 0

Synchronization of Two-Layer Multi-Weighted Networks by Finite-Time Privacy Protection 基于有限时间隐私保护的两层多加权网络同步

IF 18.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-09-01 Epub Date: 2026-10-01 DOI: 10.1109/JAS.2026.125936

Yuhua Xu;Mengna Liu;Wei Xing Zheng;Xiaoqun Wu

引用次数: 0

Consensus Evaluation of Multi-Agent-Based Distributed Load Frequency Control with Time-Varying Delays and Communication Topologies 时变时延和通信拓扑下基于多智能体的分布式负荷频率控制的一致性评估

IF 18.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-09-01 Epub Date: 2026-09-29 DOI: 10.1109/JAS.2025.125651

Xing-Chen Shangguan;Jia-Ju Shen;Yong He;Chuan-Ke Zhang

引用次数: 0

Towards Efficient Intrusion Detection: A Bayesian Nonparametric Model with Gamma Distributions 迈向高效入侵检测：一个具有Gamma分布的贝叶斯非参数模型

IF 18.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-09-01 Epub Date: 2026-09-29 DOI: 10.1109/JAS.2026.125927

Yuping Lai;Zidong Wang;Jiahan Dong;Yongcai Xiao;Zihao Li;Qing Ye

{"title":"Towards Efficient Intrusion Detection: A Bayesian Nonparametric Model with Gamma Distributions","authors":"Yuping Lai;Zidong Wang;Jiahan Dong;Yongcai Xiao;Zihao Li;Qing Ye","doi":"10.1109/JAS.2026.125927","DOIUrl":"https://doi.org/10.1109/JAS.2026.125927","url":null,"abstract":"With the continuous development and widespread application of internet technology, network security issues have become increasingly complex and dynamic. To address these challenges, intrusion detection technology has emerged as a research hotspot in cyberspace security. Finite mixture models have been widely adopted for network intrusion detection; however, existing studies have predominantly focused on parameter estimation, while often neglecting the effects of model selection and data imbalance, which can lead to suboptimal detection performance. To address this limitation, in this paper, we first employ oversampling approaches to generate a rebalanced training set. Subsequently, a Dirichlet process mixture of gamma distributions based on a stick-breaking representation is utilized to model the underlying distributions of normal and suspicious activities. The proposed model is then trained using the extended stochastic variational inference framework, through which an analytically tractable solution for Bayesian estimation is developed. This learning strategy enables the simultaneous estimation of model complexity and parameters within a unified Bayesian framework. The effectiveness and performance of the proposed method are validated on three publicly available datasets, namely, UNSW-NB 15, CICIoT2023, and ISCX-IDS-2012. In comparison with several well-established finite mixture models, as well as machine learning and deep learning algorithms, the proposed approach not only achieves comparable or superior detection performance in terms of precision, recall, F1 score, and AUC values, but also significantly reduces training and detection time.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"13 9","pages":"2132-2145"},"PeriodicalIF":18.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149072314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

LSTM Networks-Based Data-Driven Secure Synchronization of Interconnected Systems with Malicious Subsystems 基于LSTM网络的具有恶意子系统的互联系统数据驱动安全同步

IF 18.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-09-01 Epub Date: 2026-09-29 DOI: 10.1109/JAS.2026.125933

Xuan Jia;Junfeng Zhang;Baozhu Du;Haoyue Yang;Uzair Aslam Bhatti

引用次数: 0

Model-Free Adaptive Learning Control with Prescribed Performance of Nonlinear Systems 非线性系统预定性能的无模型自适应学习控制

IF 18.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2026-09-01 Epub Date: 2026-09-29 DOI: 10.1109/JAS.2026.125885

Yong-Sheng Ma;Wei-Wei Che;Zheng-Guang Wu

引用次数: 0