International Journal of Adaptive Control and Signal Processing最新文献_第10页

Online identification of Hammerstein systems with B-spline networks 利用 B-样条网络在线识别哈默斯坦系统

IF 3.1 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-03-27 DOI: 10.1002/acs.3792

Yanjiao Wang, Yiting Liu, Jiehao Chen, Shihua Tang, Muqing Deng

引用次数: 0

Event-triggered adaptive secure lateral stabilization for autonomous vehicles under actuator attacks 致动器攻击下自动驾驶车辆的事件触发自适应安全横向稳定功能

IF 3.1 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-03-24 DOI: 10.1002/acs.3797

Hong-Tao Sun, Xinran Chen, Yitao Shen, Chen Peng, Jiwei Zhao

{"title":"Event-triggered adaptive secure lateral stabilization for autonomous vehicles under actuator attacks","authors":"Hong-Tao Sun, Xinran Chen, Yitao Shen, Chen Peng, Jiwei Zhao","doi":"10.1002/acs.3797","DOIUrl":"10.1002/acs.3797","url":null,"abstract":"<div>\u0000 \u0000 <p>False data injection attacks can disrupt the steering control actions and make a real threat to both the security and safety of autonomous vehicles. In this paper, a secure event-triggered lateral control approach of autonomous vehicles subject to actuator attacks is investigated. Firstly, an arbitrary unknown actuator attacks is considered in the secure lateral steering control of autonomous vehicles. Thus, to save communication resources for the limited bandwidth CAN bus, the periodic event-triggered transmission scheme is utilized, transforming the established lateral steering control into a time-delay system through the consideration of periodic event-triggered sampling. Then, an adaptive control compensation scheme is developed to mitigate the malicious effects caused by actuator attacks. The proposed secure control approach is skilled in compensating the unknown attacked steering control actions in an adaptive way. The stabilization criteria under the adaptive secure control law is well derived by Lyapunov–Krasovskii method and some linear inequality matrices operations. At last, the effectiveness of the proposed secure control scheme is verified by some numerical experiments borrowed from a practical vehicle.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"38 6","pages":"2128-2143"},"PeriodicalIF":3.1,"publicationDate":"2024-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140301708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Design of distributed event-triggered states and unknown disturbances observers for time-varying delay interconnected systems 为时变延迟互联系统设计分布式事件触发状态和未知干扰观测器

IF 3.1 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-03-24 DOI: 10.1002/acs.3796

Dinh Cong Huong

{"title":"Design of distributed event-triggered states and unknown disturbances observers for time-varying delay interconnected systems","authors":"Dinh Cong Huong","doi":"10.1002/acs.3796","DOIUrl":"10.1002/acs.3796","url":null,"abstract":"<div>\u0000 \u0000 <p>This article considers the problem of designing distributed event-triggered states and unknown disturbances observers for a class of nonlinear interconnected systems where the local state vectors are affected by unknown delays and the nonlinear function satisfying the Lipschitz condition. Distributed observers are designed based on the local input vector and both the local and remote output vectors. Different from previously distributed observers for interconnected systems where the local and remote output vectors are updated continuously, the one in this article uses only information on the local and remote output vectors updating at triggering instants of proposed event-triggered mechanisms. This indicates that the proposed method in this article is better than the existing ones in saving communication resources while still keeping an acceptable estimation performance. Sufficient conditions for the existence of the proposed distributed observers are established and are formed in a convex optimization problem which can be easily solved by using the MATLAB LMI Control Toolbox. Finally, a numerical example is given to confirm the effectiveness and advantages of the proposed method.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"38 6","pages":"2144-2157"},"PeriodicalIF":3.1,"publicationDate":"2024-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140301852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Data‐driven disturbance compensation control for discrete‐time systems based on reinforcement learning 基于强化学习的离散时间系统数据驱动干扰补偿控制

IF 3.1 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-03-22 DOI: 10.1002/acs.3793

Lanyue Li, Jinna Li, Jiangtao Cao

引用次数: 0

Binary observation-based identification for finite impulse response systems under denial of service attacks 拒绝服务攻击下基于二进制观测的有限脉冲响应系统识别

IF 3.1 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-03-21 DOI: 10.1002/acs.3794

Jingliang Wei, Ruizhe Jia, Fengwei Jing, Jin Guo

引用次数: 0

Adaptive control for synchronization of time-delayed complex networks with multi-weights based on semi-linear hyperbolic PDEs 基于半线性双曲 PDE 的多权重时延复杂网络同步自适应控制

IF 3.1 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-03-20 DOI: 10.1002/acs.3780

Chengyan Yang, Jianlong Qiu

引用次数: 0

Iterative learning based convergence analysis for nonlinear impulsive differential inclusion systems with randomly varying trial lengths 基于迭代学习的收敛性分析，适用于试验长度随机变化的非线性脉冲微分包容系统

IF 3.1 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-03-17 DOI: 10.1002/acs.3791

Wanzheng Qiu, JinRong Wang, Dong Shen

{"title":"Iterative learning based convergence analysis for nonlinear impulsive differential inclusion systems with randomly varying trial lengths","authors":"Wanzheng Qiu, JinRong Wang, Dong Shen","doi":"10.1002/acs.3791","DOIUrl":"10.1002/acs.3791","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper studies the finite-time tracking problem for nonlinear impulsive differential inclusion systems with randomly varying trial lengths. First, we convert the set-valued mapping in the differential inclusion systems to single-valued mapping by a Steiner-type selector. For the tracking problem of random discontinuous output trajectories, this paper defines a piecewise continuous variable by zero-order holder to correct the tracking error of segmented continuity. Then, we introduce the average operator with forgetting factor to design three novel learning schemes, and establish convergence results by using the mathematical analysis tools such as impulsive Gronwall inequality and <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>λ</mi>\u0000 </mrow>\u0000 <annotation>$$ lambda $$</annotation>\u0000 </semantics></math>-norm. Finally, a numerical example verifies the validity of the theoretical results, and we compare the tracking performance of the output trajectories for different forgetting factors.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"38 6","pages":"2056-2073"},"PeriodicalIF":3.1,"publicationDate":"2024-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140153442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Cluster synchronization of stochastic two-layer networks with infinite distributed delays via delayed pinning impulsive control 通过延迟针刺脉冲控制实现具有无限分布延迟的随机双层网络的簇同步

IF 3.1 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-03-15 DOI: 10.1002/acs.3795

Chuan Zhang, Junchao Wei, Fei Wang, Yi Liang

引用次数: 0

Adaptive finite-time optimal time-varying formation control for second-order stochastic nonlinear multiagent systems 二阶随机非线性多代理系统的自适应有限时间最优时变编队控制

IF 3.1 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-03-13 DOI: 10.1002/acs.3788

Jiaxin Zhang, Yue Fu, Jun Fu

引用次数: 0

Intrusion detection system based on the beetle swarm optimization and K-RMS clustering algorithm 基于甲虫群优化和 K-RMS 聚类算法的入侵检测系统

IF 3.1 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-03-12 DOI: 10.1002/acs.3771

S. Gokul Pran, Sivakami Raja, S. Jeyasudha

{"title":"Intrusion detection system based on the beetle swarm optimization and K-RMS clustering algorithm","authors":"S. Gokul Pran, Sivakami Raja, S. Jeyasudha","doi":"10.1002/acs.3771","DOIUrl":"10.1002/acs.3771","url":null,"abstract":"<div>\u0000 \u0000 <p>Intrusion detection is a cyber-security method that is significant for network security. It is utilized to detect behaviors that compromise security and privacy within a network or in the context of a computer system. To enhance the identification, an Intrusion Detection System Based on the Beetle Swarm Optimization and K-RMS Clustering Algorithm cluster-based hybrid classifiers is proposed in this manuscript. Here, the data is amassed from CICIDS2017 dataset. Then the data is preprocessed to eradicate the unwanted noise. After completing the preprocessed data, it can be clustered by using K-RMS clustering algorithm. This algorithm cluster the entire data to the associated cluster set depending on the data behavior. The classification algorithm is considered to predict the data as normal or attacking behaviors. The hybrid classification is used to predict the data. The solitary predictor aims to achieve high detection rates and accuracy. The hybrid classifiers, such as support vector machines, artificial neural networks are applied to recognize the normal or intruder. The performance of the SVM-ANN-IDS method attains 22.05%, 15.87%, 27.25% higher accuracy, 23.90% and 28.53% higher precision, 29.29%, 19.19% and 23.27% higher specificity and 18.28%, 24.36% and 27.49% greater recall when compared to the existing models, like developing novel deep-learning model to improve network intrusion categorization (DNN-IDS), Intrusion identification scheme on real-time data traffic under machine learning techniques along feature selection method (RNN-SVM-IDS) and recurrent deep learning basis feature fusion ensemble meta-classifier for intellectual network intrusion identification scheme (RNN-IDS) respectively.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"38 5","pages":"1675-1689"},"PeriodicalIF":3.1,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140125743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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