Ieee-Caa Journal of Automatica Sinica最新文献_第10页

Enhanced Tube-Based Event-Triggered Stochastic Model Predictive Control with Additive Uncertainties 具有可加性不确定性的增强管型事件触发随机模型预测控制

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-03-03 DOI: 10.1109/JAS.2024.124974

Chenxi Gu;Xinli Wang;Kang Li;Xiaohong Yin;Shaoyuan Li;Lei Wang

{"title":"Enhanced Tube-Based Event-Triggered Stochastic Model Predictive Control with Additive Uncertainties","authors":"Chenxi Gu;Xinli Wang;Kang Li;Xiaohong Yin;Shaoyuan Li;Lei Wang","doi":"10.1109/JAS.2024.124974","DOIUrl":"https://doi.org/10.1109/JAS.2024.124974","url":null,"abstract":"This paper proposes an event-triggered stochastic model predictive control for discrete-time linear time-invariant (LTI) systems under additive stochastic disturbances. It first constructs a probabilistic invariant set and a probabilistic reachable set based on the priori knowledge of system uncertainties. Assisted with enhanced robust tubes, the chance constraints are then formulated into a deterministic form. To alleviate the online computational burden, a novel event-triggered stochastic model predictive control is developed, where the triggering condition is designed based on the past and future optimal trajectory tracking errors in order to achieve a good trade-off between system resource utilization and control performance. Two triggering parameters σ and γ are used to adjust the frequency of solving the optimization problem. The probabilistic feasibility and stability of the system under the event-triggered mechanism are also examined. Finally, numerical studies on the control of a heating, ventilation, and air conditioning (HVAC) system confirm the efficacy of the proposed control.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 3","pages":"596-605"},"PeriodicalIF":15.3,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143535555","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

Fixed-Time Stability of Random Nonlinear Systems 随机非线性系统的定时稳定性

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-01-31 DOI: 10.1109/JAS.2024.124353

Fuyong Wang;Jiayi Gong;Zhongxin Liu;Fei Chen

引用次数: 0

Global Sampled-Data Output Feedback Stabilization for Nonlinear Systems via Intermittent Hold 基于间歇保持的非线性系统的全局采样数据输出反馈镇定

IF 19.2 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-01-31 DOI: 10.1109/JAS.2024.125019

Le Chang;Cheng Fu;Huanjun Zhang

引用次数: 0

Variable Reconstruction for Evolutionary Expensive Large-Scale Multiobjective Optimization and Its Application on Aerodynamic Design 演化昂贵大规模多目标优化的变量重构及其在气动设计中的应用

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-01-31 DOI: 10.1109/JAS.2024.124947

Jianqing Lin;Cheng He;Ye Tian;Linqiang Pan

{"title":"Variable Reconstruction for Evolutionary Expensive Large-Scale Multiobjective Optimization and Its Application on Aerodynamic Design","authors":"Jianqing Lin;Cheng He;Ye Tian;Linqiang Pan","doi":"10.1109/JAS.2024.124947","DOIUrl":"https://doi.org/10.1109/JAS.2024.124947","url":null,"abstract":"Expensive multiobjective optimization problems (EMOPs) are complex optimization problems exacted from real-world applications, where each objective function evaluation (FE) involves expensive computations or physical experiments. Many surrogate-assisted evolutionary algorithms (SAEAs) have been designed to solve EMOPs. Nevertheless, EMOPs with large-scale decision variables remain challenging for existing SAEAs, leading to difficulties in maintaining convergence and diversity. To address this deficiency, we proposed a variable reconstruction-based SAEA (VREA) to balance convergence enhancement and diversity maintenance. Generally, a cluster-based variable reconstruction strategy reconstructs the original large-scale decision variables into low-dimensional weight variables. Thus, the population can be rapidly pushed towards the Pareto set (PS) by optimizing low-dimensional weight variables with the assistance of surrogate models. Population diversity is improved due to the cluster-based variable reconstruction strategy. An adaptive search step size strategy is proposed to balance exploration and exploitation further. Experimental comparisons with four state-of-the-art SAEAs are conducted on benchmark EMOPs with up to 1000 decision variables and an aerodynamic design task. Experimental results demonstrate that VREA obtains well-converged and diverse solutions with limited real FEs.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 4","pages":"719-733"},"PeriodicalIF":15.3,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143740230","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

Self-Cumulative Contrastive Graph Clustering 自累积对比图聚类

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-01-31 DOI: 10.1109/JAS.2024.125025

Xiaoqiang Yan;Kun Deng;Quan Zou;Zhen Tian;Hui Yu

{"title":"Self-Cumulative Contrastive Graph Clustering","authors":"Xiaoqiang Yan;Kun Deng;Quan Zou;Zhen Tian;Hui Yu","doi":"10.1109/JAS.2024.125025","DOIUrl":"https://doi.org/10.1109/JAS.2024.125025","url":null,"abstract":"Contrastive graph clustering (CGC) has become a prominent method for self-supervised representation learning by contrasting augmented graph data pairs. However, the performance of CGC methods critically depends on the choice of data augmentation, which usually limits the capacity of network generalization. Besides, most existing methods characterize positive and negative samples based on the nodes themselves, ignoring the influence of neighbors with different hop numbers on the node. In this study, a novel self-cumulative contrastive graph clustering (SC-CGC) method is devised, which is capable of dynamically adjusting the influence of neighbors with different hops. Our intuition is that better neighbors are closer and distant ones are further away in their feature space, thus we can perform neighbor contrasting without data augmentation. To be specific, SC-CGC relies on two neural networks, i.e., autoencoder network (AE) and graph autoencoder network (GAE), to encode the node information and graph structure, respectively. To make these two networks interact and learn from each other, a dynamic fusion mechanism is devised to transfer the knowledge learned by AE to the corresponding GAE layer by layer. Then, a self-cumulative contrastive loss function is designed to characterize the structural information by dynamically accumulating the influence of the nodes with different hops. Finally, our approach simultaneously refines the representation learning and clustering assignments in a self-supervised manner. Extensive experiments on 8 realistic datasets demonstrate that SC-CGC consistently performs better over SOTA techniques. The code is available at https://github.com/Xiaoqiang-Yan/JAS-SCCGC.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 6","pages":"1194-1208"},"PeriodicalIF":15.3,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144281312","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

Length-Variable Bionic Continuum Robot with Millimeter-Scale Diameter and Compliant Driving Force 具有毫米级直径和柔性驱动力的可变长度仿生连续体机器人

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-01-31 DOI: 10.1109/JAS.2024.125091

Shiying Zhao;Qingxin Meng;Xuzhi Lai;Jinhua She;Edwardo Fumihiko Fukushima;Min Wu

{"title":"Length-Variable Bionic Continuum Robot with Millimeter-Scale Diameter and Compliant Driving Force","authors":"Shiying Zhao;Qingxin Meng;Xuzhi Lai;Jinhua She;Edwardo Fumihiko Fukushima;Min Wu","doi":"10.1109/JAS.2024.125091","DOIUrl":"https://doi.org/10.1109/JAS.2024.125091","url":null,"abstract":"Compared with conventional rigid-link robots, bionic continuum robots (CRs) show great potential in unstructured environments because of their adaptivity and continuous deformation ability. However, designing a CR to achieve miniaturization, variable length and compliant driving force remains a challenge. Here, inspired by the earthworm in nature, we report a length-variable bionic CR with millimeter-scale diameter and compliant driving force. The CR consists of two main components: the robot body and soft drives. The robot body is only 6 mm in diameter, and is composed of a backbone and transmission devices. The backbone is divided into three segments, and each segment is capable of adjusting its length and bending like the earthworm. The maximum length variation of the backbone can reach an astonishing 70 mm with a backbone's initial length of 150 mm, and the maximum bending angle of each segment can reach 120 degrees. In addition, we develop soft drives using pneumatic soft actuators (PSAs) as a replacement for the rigid motors typically used in conventional CRs. These soft drives control the motions of the transmission devices, enabling length variation and bending of the backbone. By utilizing these soft drives, we ensure that the robot body has a compliant driving force, which addresses users' concerns about human safety during interactions. In practical applications, we prove that this CR can perform delicate manipulations by successfully completing writing tasks. Additionally, we show its application value for detections and medical treatments by entering the narrow tube and the oral.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 4","pages":"655-667"},"PeriodicalIF":15.3,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143740191","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

Deep Reinforcement Learning for Zero-Shot Coverage Path Planning With Mobile Robots 移动机器人零射击覆盖路径规划的深度强化学习

IF 19.2 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-01-31 DOI: 10.1109/JAS.2024.125064

José Pedro Carvalho;A. Pedro Aguiar

{"title":"Deep Reinforcement Learning for Zero-Shot Coverage Path Planning With Mobile Robots","authors":"José Pedro Carvalho;A. Pedro Aguiar","doi":"10.1109/JAS.2024.125064","DOIUrl":"https://doi.org/10.1109/JAS.2024.125064","url":null,"abstract":"The ability of mobile robots to plan and execute a path is foundational to various path-planning challenges, particularly Coverage Path Planning. While this task has been typically tackled with classical algorithms, these often struggle with flexibility and adaptability in unknown environments. On the other hand, recent advances in Reinforcement Learning offer promising approaches, yet a significant gap in the literature remains when it comes to generalization over a large number of parameters. This paper presents a unified, generalized framework for coverage path planning that leverages value-based deep reinforcement learning techniques. The novelty of the framework comes from the design of an observation space that accommodates different map sizes, an action masking scheme that guarantees safety and robustness while also serving as a learning-from-demonstration technique during training, and a unique reward function that yields value functions that are size-invariant. These are coupled with a curriculum learning-based training strategy and parametric environment randomization, enabling the agent to tackle complete or partial coverage path planning with perfect or incomplete knowledge while generalizing to different map sizes, configurations, sensor payloads, and sub-tasks. Our empirical results show that the algorithm can perform zero-shot learning scenarios at a near-optimal level in environments that follow a similar distribution as during training, outperforming a greedy heuristic by sixfold. Furthermore, in out-of-distribution environments, our method surpasses existing state-of-the-art algorithms in most zero-shot and all few-shot scenarios, paving the way for generalizable and adaptable path-planning algorithms.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 8","pages":"1594-1609"},"PeriodicalIF":19.2,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144880625","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

Predefined-Time Constrained Optimization of MultiAgent Systems Under Impulsive Effects 脉冲效应下多智能体系统的预定义时间约束优化

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-01-22 DOI: 10.1109/JAS.2024.124710

Zhuyan Jiang;Xiaoyang Liu;Xiang Jiang;Jinde Cao

引用次数: 0

Online Fault-Tolerant Tracking Control With Adaptive Critic for Nonaffine Nonlinear Systems 非仿射非线性系统的自适应在线容错跟踪控制

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-01-22 DOI: 10.1109/JAS.2024.124989

Ding Wang;Lingzhi Hu;Xiaoli Li;Junfei Qiao

{"title":"Online Fault-Tolerant Tracking Control With Adaptive Critic for Nonaffine Nonlinear Systems","authors":"Ding Wang;Lingzhi Hu;Xiaoli Li;Junfei Qiao","doi":"10.1109/JAS.2024.124989","DOIUrl":"https://doi.org/10.1109/JAS.2024.124989","url":null,"abstract":"In this paper, a fault-tolerant-based online critic learning algorithm is developed to solve the optimal tracking control issue for nonaffine nonlinear systems with actuator faults. First, a novel augmented plant is constructed by fusing the system state and the reference trajectory, which aims to transform the optimal fault-tolerant tracking control design with actuator faults into the optimal regulation problem of the conventional nonlinear error system. Subsequently, in order to ensure the normal execution of the online learning algorithm, a stability criterion condition is created to obtain an initial admissible tracking policy. Then, the constructed model neural network (NN) is pre-trained to recognize the system dynamics and calculate trajectory control. The critic and action NNs are constructed to output the approximate cost function and approximate tracking control, respectively. The Hamilton-Jacobi-Bellman equation of the error system is solved online through the action-critic framework. In theoretical analysis, it is proved that all concerned signals are uniformly ultimately bounded according to the Lyapunov principle. The tracking control law can approach the optimal tracking control within a finite approximation error. Finally, two experimental examples are conducted to indicate the effectiveness and supe-riority of the developed fault-tolerant tracking control scheme.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 1","pages":"215-227"},"PeriodicalIF":15.3,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993524","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

GPIO-Based Continuous Sliding Mode Control for Networked Control Systems Under Communication Delays with Experiments on Servo Motors 通信延迟下基于gpio的网络控制系统连续滑模控制与伺服电机实验

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-01-22 DOI: 10.1109/JAS.2024.124812

Kamal Rsetam;Zhenwei Cao;Zhihong Man;Xian-Ming Zhang

{"title":"GPIO-Based Continuous Sliding Mode Control for Networked Control Systems Under Communication Delays with Experiments on Servo Motors","authors":"Kamal Rsetam;Zhenwei Cao;Zhihong Man;Xian-Ming Zhang","doi":"10.1109/JAS.2024.124812","DOIUrl":"https://doi.org/10.1109/JAS.2024.124812","url":null,"abstract":"To handle input and output time delays that com-monly exist in many networked control systems (NCSs), a new robust continuous sliding mode control (CSMC) scheme is proposed for the output tracking in uncertain single input-single-out-put (SISO) networked control systems. This scheme consists of three consecutive steps. First, although the network-induced delay in those systems can be effectively handled by using Pade approximation (PA), the unmatched disturbance cames out as another difficulty in the control design. Second, to actively estimate this unmatched disturbance, a generalized proportional integral observer (GPIO) technique is utilized based on only one measured state. Third, by constructing a new sliding manifold with the aid of the estimated unmatched disturbance and states, a GPIO-based CSMC is synthesized, which is employed to cope with not only matched and unmatched disturbances, but also net-work-induced delays. The stability of the entire closed-loop system under the proposed GPIO-based CSMC is detailedly analyzed. The promising tracking efficiency and feasibility of the proposed control methodology are verified through simulations and experiments on Quanser's servo module for motion control under various test conditions.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 1","pages":"99-113"},"PeriodicalIF":15.3,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993542","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