Ieee-Caa Journal of Automatica Sinica最新文献_第4页

Distributed Predefined-Time Control for Cooperative Tracking of Multiple Quadrotor UAVs 用于多架四旋翼无人飞行器合作跟踪的分布式预定义时间控制

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-09-04 DOI: 10.1109/JAS.2023.123861

Kewei Xia;Xinyi Li;Kaidan Li;Yao Zou

引用次数: 0

Evolution and Role of Optimizers in Training Deep Learning Models 优化器在训练深度学习模型中的演变和作用

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-09-04 DOI: 10.1109/JAS.2024.124806

XiaoHao Wen;MengChu Zhou

引用次数: 0

Hierarchical Controller Synthesis Under Linear Temporal Logic Specifications Using Dynamic Quantization 利用动态量化在线性时态逻辑规范下合成分层控制器

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-09-04 DOI: 10.1109/JAS.2024.124473

Wei Ren;Zhuo-Rui Pan;Weiguo Xia;Xi-Ming Sun

{"title":"Hierarchical Controller Synthesis Under Linear Temporal Logic Specifications Using Dynamic Quantization","authors":"Wei Ren;Zhuo-Rui Pan;Weiguo Xia;Xi-Ming Sun","doi":"10.1109/JAS.2024.124473","DOIUrl":"https://doi.org/10.1109/JAS.2024.124473","url":null,"abstract":"Linear temporal logic (LTL) is an intuitive and expressive language to specify complex control tasks, and how to design an efficient control strategy for LTL specification is still a challenge. In this paper, we implement the dynamic quantization technique to propose a novel hierarchical control strategy for nonlinear control systems under LTL specifications. Based on the regions of interest involved in the LTL formula, an accepting path is derived first to provide a high-level solution for the controller synthesis problem. Second, we develop a dynamic quantization based approach to verify the realization of the accepting path. The realization verification results in the necessity of the controller design and a sequence of quantization regions for the controller design. Third, the techniques of dynamic quantization and abstraction-based control are combined together to establish the local-to-global control strategy. Both abstraction construction and controller design are local and dynamic, thereby resulting in the potential reduction of the computational complexity. Since each quantization region can be considered locally and individually, the proposed hierarchical mechanism is more efficient and can solve much larger problems than many existing methods. Finally, the proposed control strategy is illustrated via two examples from the path planning and tracking problems of mobile robots.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"11 10","pages":"2082-2098"},"PeriodicalIF":15.3,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137597","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

High-Order Control Barrier Function-Based Safety Control of Constrained Robotic Systems: An Augmented Dynamics Approach 基于高阶控制障碍函数的受约束机器人系统安全控制：增强动力学方法

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-09-04 DOI: 10.1109/JAS.2024.124524

Haijing Wang;Jinzhu Peng;Fangfang Zhang;Yaonan Wang

{"title":"High-Order Control Barrier Function-Based Safety Control of Constrained Robotic Systems: An Augmented Dynamics Approach","authors":"Haijing Wang;Jinzhu Peng;Fangfang Zhang;Yaonan Wang","doi":"10.1109/JAS.2024.124524","DOIUrl":"https://doi.org/10.1109/JAS.2024.124524","url":null,"abstract":"Although constraint satisfaction approaches have achieved fruitful results, system states may lose their smoothness and there may be undesired chattering of control inputs due to switching characteristics. Furthermore, it remains a challenge when there are additional constraints on control torques of robotic systems. In this article, we propose a novel high-order control barrier function (HoCBF)-based safety control method for robotic systems subject to input-output constraints, which can maintain the desired smoothness of system states and reduce undesired chattering vibration in the control torque. In our design, augmented dynamics are introduced into the HoCBF by constructing its output as the control input of the robotic system, so that the constraint satisfaction is facilitated by HoCBFs and the smoothness of system states is maintained by the augmented dynamics. This proposed scheme leads to the quadratic program (QP), which is more user-friendly in implementation since the constraint satisfaction control design is implemented as an add-on to an existing tracking control law. The proposed closed-loop control system not only achieves the requirements of real-time capability, stability, safety and compliance, but also reduces undesired chattering of control inputs. Finally, the effectiveness of the proposed control scheme is verified by simulations and experiments on robotic manipulators.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"11 12","pages":"2487-2496"},"PeriodicalIF":15.3,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142679274","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

Dynamic Vision-Based Machinery Fault Diagnosis with Cross-Modality Feature Alignment 基于视觉的动态机械故障诊断与跨模态特征对齐

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-09-04 DOI: 10.1109/JAS.2024.124470

Xiang Li;Shupeng Yu;Yaguo Lei;Naipeng Li;Bin Yang

{"title":"Dynamic Vision-Based Machinery Fault Diagnosis with Cross-Modality Feature Alignment","authors":"Xiang Li;Shupeng Yu;Yaguo Lei;Naipeng Li;Bin Yang","doi":"10.1109/JAS.2024.124470","DOIUrl":"https://doi.org/10.1109/JAS.2024.124470","url":null,"abstract":"Intelligent machinery fault diagnosis methods have been popularly and successfully developed in the past decades, and the vibration acceleration data collected by contact accelerometers have been widely investigated. In many industrial scenarios, contactless sensors are more preferred. The event camera is an emerging bio-inspired technology for vision sensing, which asynchronously records per-pixel brightness change polarity with high temporal resolution and low latency. It offers a promising tool for contactless machine vibration sensing and fault diagnosis. However, the dynamic vision-based methods suffer from variations of practical factors such as camera position, machine operating condition, etc. Furthermore, as a new sensing technology, the labeled dynamic vision data are limited, which generally cannot cover a wide range of machine fault modes. Aiming at these challenges, a novel dynamic vision-based machinery fault diagnosis method is proposed in this paper. It is motivated to explore the abundant vibration acceleration data for enhancing the dynamic vision-based model performance. A cross-modality feature alignment method is thus proposed with deep adversarial neural networks to achieve fault diagnosis knowledge transfer. An event erasing method is further proposed for improving model robustness against variations. The proposed method can effectively identify unseen fault mode with dynamic vision data. Experiments on two rotating machine monitoring datasets are carried out for validations, and the results suggest the proposed method is promising for generalized contactless machinery fault diagnosis.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"11 10","pages":"2068-2081"},"PeriodicalIF":15.3,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137595","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

Bridge Bidding via Deep Reinforcement Learning and Belief Monte Carlo Search 通过深度强化学习和信念蒙特卡洛搜索进行桥牌竞价

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-09-04 DOI: 10.1109/JAS.2024.124488

Zizhang Qiu;Shouguang Wang;Dan You;MengChu Zhou

引用次数: 0

Urban Traffic Control Meets Decision Recommendation System: A Survey and Perspective 城市交通管制与决策建议系统：调查与展望

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-09-04 DOI: 10.1109/JAS.2024.124659

Qingyuan Ji;Xiaoyue Wen;Junchen Jin;Yongdong Zhu;Yisheng Lv

{"title":"Urban Traffic Control Meets Decision Recommendation System: A Survey and Perspective","authors":"Qingyuan Ji;Xiaoyue Wen;Junchen Jin;Yongdong Zhu;Yisheng Lv","doi":"10.1109/JAS.2024.124659","DOIUrl":"https://doi.org/10.1109/JAS.2024.124659","url":null,"abstract":"Urban traffic control is a multifaceted and demanding task that necessitates extensive decision-making to ensure the safety and efficiency of urban transportation systems. Traditional approaches require traffic signal professionals to manually intervene on traffic control devices at the intersection level, utilizing their knowledge and expertise. However, this process is cumbersome, labor-intensive, and cannot be applied on a large network scale. Recent studies have begun to explore the applicability of recommendation system for urban traffic control, which offer increased control efficiency and scalability. Such a decision recommendation system is complex, with various interdependent components, but a systematic literature review has not yet been conducted. In this work, we present an up-to-date survey that elucidates all the detailed components of a recommendation system for urban traffic control, demonstrates the utility and efficacy of such a system in the real world using data and knowledge-driven approaches, and discusses the current challenges and potential future directions of this field.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"11 10","pages":"2043-2058"},"PeriodicalIF":15.3,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137523","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

Neural Network-Based State Estimation for Nonlinear Systems with Denial-of-Service Attack Under Try-Once-Discard Protocol 基于神经网络的拒绝服务攻击非线性系统状态估计（试一试协议下

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-09-04 DOI: 10.1109/JAS.2023.123690

Xueli Wang;Shangwei Zhao;Ming Yang;Xin Wang;Xiaoming Wu

引用次数: 0

Scalable Temporal Dimension Preserved Tensor Completion for Missing Traffic Data Imputation with Orthogonal Initialization 利用正交初始化对缺失交通数据进行可扩展的时空维度保留张量补全

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-09-04 DOI: 10.1109/JAS.2024.124278

Hong Chen;Mingwei Lin;Jiaqi Liu;Zeshui Xu

{"title":"Scalable Temporal Dimension Preserved Tensor Completion for Missing Traffic Data Imputation with Orthogonal Initialization","authors":"Hong Chen;Mingwei Lin;Jiaqi Liu;Zeshui Xu","doi":"10.1109/JAS.2024.124278","DOIUrl":"https://doi.org/10.1109/JAS.2024.124278","url":null,"abstract":"Dear Editor, This letter puts forward a novel scalable temporal dimension preserved tensor completion model based on orthogonal initialization for missing traffic data (MTD) imputation. The MTD imputation acts directly on accessing the traffic state, and affects the traffic management. However, it still faces the following challenges: 1) The MTD imputation is usually formulated as matrix completion or tensor completion, which ignores the information across different dimensions; 2) Most of the existing models cannot generalize to traffic datasets of different scales or different missing rates; and 3) The MTD imputation models based on Gaussian random initialization easily leads to gradient explosion or vanishing, so that the training accuracy is not effectively improved. Inspired by these findings, the proposed scalable temporal dimension preserved tensor completion (ST-DPTC) model creatively establishes the following three-fold ideas: a) Incorporating the dimension preserved tensor completion (DPTC) to extract more distinctive traffic structure changes from the low-rank latent factor tensors; b) Adopting a scalable temporal (ST) regularization with first-order difference and second-order difference operators to adapt to different scales of traffic data; and c) Embedding ST regularization into DPTC with orthogonal initialization to perform low-rank latent factor tensor extraction and MTD imputation. Results on real-world traffic datasets with different scales show that our proposed model exceeds the state-of-the-art models in terms of the imputation accuracy.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"11 10","pages":"2188-2190"},"PeriodicalIF":15.3,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10664599","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137608","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

Safe Q-Learning for Data-Driven Nonlinear Optimal Control with Asymmetric State Constraints 具有非对称状态约束的数据驱动非线性优化控制的安全 Q 学习

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-09-04 DOI: 10.1109/JAS.2024.124509

Mingming Zhao;Ding Wang;Shijie Song;Junfei Qiao

{"title":"Safe Q-Learning for Data-Driven Nonlinear Optimal Control with Asymmetric State Constraints","authors":"Mingming Zhao;Ding Wang;Shijie Song;Junfei Qiao","doi":"10.1109/JAS.2024.124509","DOIUrl":"https://doi.org/10.1109/JAS.2024.124509","url":null,"abstract":"This article develops a novel data-driven safe Q-learning method to design the safe optimal controller which can guarantee constrained states of nonlinear systems always stay in the safe region while providing an optimal performance. First, we design an augmented utility function consisting of an adjustable positive definite control obstacle function and a quadratic form of the next state to ensure the safety and optimality. Second, by exploiting a pre-designed admissible policy for initialization, an off-policy stabilizing value iteration Q-learning (SVIQL) algorithm is presented to seek the safe optimal policy by using offline data within the safe region rather than the mathematical model. Third, the monotonicity, safety, and optimality of the SVIQL algorithm are theoretically proven. To obtain the initial admissible policy for SVIQL, an offline VIQL algorithm with zero initialization is constructed and a new admissibility criterion is established for immature iterative policies. Moreover, the critic and action networks with precise approximation ability are established to promote the operation of VIQL and SVIQL algorithms. Finally, three simulation experiments are conducted to demonstrate the virtue and superiority of the developed safe Q-learning method.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"11 12","pages":"2408-2422"},"PeriodicalIF":15.3,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142679333","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