The exact feedback linearization method implies an accurate knowledge of the model and its parameters. This assumption is an inherent limitation of the method, suffering from robustness issues. In general, the model structure is only partially known and its parameters present uncertainties. The current paper extends the classical exact feedback linearization to the robust feedback linearization by adding an appropriately-designed robust control layer. This is then able to ensure robust stability and robust performance for the given uncertain system in a desired region of attraction. We consider the case of full relative degree input-affine nonlinear systems, which are of great practical importance in the literature. The inner loop contains the feedback linearization input for the nominal system and the resulting residual nonlinearities can always be characterized as inverse additive uncertainties. The constructive proofs provide exact representations of the uncertainty models in three considered scenarios: unmatched, fully-matched, and partially-matched uncertainties. The uncertainty model will be a descriptor system, which also represents one of the novelties of the paper. Our approach leads to a simplified control structure and a less conservative coverage of the uncertainty set compared to current alter-natives. The end-to-end procedure is emphasized on an illustrative example, in two different hypotheses.
{"title":"Fixed-Structure Robust Feedback Linearization for Full Relative Degree Nonlinear Systems","authors":"Vlad Mihaly;Mircea Şuşcă;Petru Dobra","doi":"10.1109/JAS.2025.125354","DOIUrl":"https://doi.org/10.1109/JAS.2025.125354","url":null,"abstract":"The exact feedback linearization method implies an accurate knowledge of the model and its parameters. This assumption is an inherent limitation of the method, suffering from robustness issues. In general, the model structure is only partially known and its parameters present uncertainties. The current paper extends the classical exact feedback linearization to the robust feedback linearization by adding an appropriately-designed robust control layer. This is then able to ensure robust stability and robust performance for the given uncertain system in a desired region of attraction. We consider the case of full relative degree input-affine nonlinear systems, which are of great practical importance in the literature. The inner loop contains the feedback linearization input for the nominal system and the resulting residual nonlinearities can always be characterized as inverse additive uncertainties. The constructive proofs provide exact representations of the uncertainty models in three considered scenarios: unmatched, fully-matched, and partially-matched uncertainties. The uncertainty model will be a descriptor system, which also represents one of the novelties of the paper. Our approach leads to a simplified control structure and a less conservative coverage of the uncertainty set compared to current alter-natives. The end-to-end procedure is emphasized on an illustrative example, in two different hypotheses.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 10","pages":"2026-2039"},"PeriodicalIF":19.2,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145428940","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}
A high-order fully actuated (HOFA) control method is developed for underactuated mechanical systems (UMSs) with model uncertainties and external disturbances. First, a model transformation is made from the original to a pseudo strict-feed-back form, and an HOFA model is established by using the method of variable elimination. Then, a group of high-order extended state observers (ESOs) are designed to deal with model uncertainties and external disturbances. The HOFA model is further classified and decomposed to achieve output constraints within a finite time range, and a barrier function is designed by combining with a shift function. Additionally, an ESO-based HOFA tracking control strategy for UMS is proposed. Finally, a manipulator model is used to verify the effectiveness of the proposed control strategy.
{"title":"A High-Order Fully Actuated-Based Backstepping Tracking Scheme of Underactuated Systems","authors":"Yuxin Feng;Yang Liu;Zhaoshui He;Hongyi Li","doi":"10.1109/JAS.2025.125174","DOIUrl":"https://doi.org/10.1109/JAS.2025.125174","url":null,"abstract":"A high-order fully actuated (HOFA) control method is developed for underactuated mechanical systems (UMSs) with model uncertainties and external disturbances. First, a model transformation is made from the original to a pseudo strict-feed-back form, and an HOFA model is established by using the method of variable elimination. Then, a group of high-order extended state observers (ESOs) are designed to deal with model uncertainties and external disturbances. The HOFA model is further classified and decomposed to achieve output constraints within a finite time range, and a barrier function is designed by combining with a shift function. Additionally, an ESO-based HOFA tracking control strategy for UMS is proposed. Finally, a manipulator model is used to verify the effectiveness of the proposed control strategy.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 10","pages":"2127-2137"},"PeriodicalIF":19.2,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145428887","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}
Min Wang;Yike Wang;Xiao Chen;Lu Liu;MengChu Zhou;Xiaobing Sun;Shanchen Pang
Data-flow errors are prevalent in cyber-physical systems (CPS). Although various approaches based on business process modeling notation (BPMN) have been devised for CPS modeling, the absence of formal specifications complicates the verification of data-flow. Formal techniques such as Petri nets are popularly used for identifying data-flow errors. However, due to their interleaving semantics, they suffer from the state-space explosion problem. As an unfolding method for Petri nets, the merged process (MP) technique can well represent concurrency relationships and thus be used to address this issue. Yet generating MP is complex and incurs substantial overhead. By designing and applying $alpha$-deletion rules for Petri nets with data (PNDs), this work simplifies MP, thus resulting in simplified MP (SMP) that is then used to identify data-flow errors. Our approach involves converting a BPMN into a PND and then constructing its SMP. The algorithms are developed to identify data-flow errors, e.g., redundant-data and lost-data ones. The proposed method enhances the efficiency and effectiveness of identifying data-flow errors in CPS. It is expected to prevent the problems caused by data-flow errors, e.g., medical malpractice and economic loss in some practical CPS. Its practicality and efficiency of the proposed method through several CPS. Its significant advantages over the state of the art are demonstrated.
{"title":"Identifying Data-Flow Errors in Cyber-Physical Systems Based on the Simplified Merged Process of Petri Nets","authors":"Min Wang;Yike Wang;Xiao Chen;Lu Liu;MengChu Zhou;Xiaobing Sun;Shanchen Pang","doi":"10.1109/JAS.2025.125549","DOIUrl":"https://doi.org/10.1109/JAS.2025.125549","url":null,"abstract":"Data-flow errors are prevalent in cyber-physical systems (CPS). Although various approaches based on business process modeling notation (BPMN) have been devised for CPS modeling, the absence of formal specifications complicates the verification of data-flow. Formal techniques such as Petri nets are popularly used for identifying data-flow errors. However, due to their interleaving semantics, they suffer from the state-space explosion problem. As an unfolding method for Petri nets, the merged process (MP) technique can well represent concurrency relationships and thus be used to address this issue. Yet generating MP is complex and incurs substantial overhead. By designing and applying <tex>$alpha$</tex>-deletion rules for Petri nets with data (PNDs), this work simplifies MP, thus resulting in simplified MP (SMP) that is then used to identify data-flow errors. Our approach involves converting a BPMN into a PND and then constructing its SMP. The algorithms are developed to identify data-flow errors, e.g., redundant-data and lost-data ones. The proposed method enhances the efficiency and effectiveness of identifying data-flow errors in CPS. It is expected to prevent the problems caused by data-flow errors, e.g., medical malpractice and economic loss in some practical CPS. Its practicality and efficiency of the proposed method through several CPS. Its significant advantages over the state of the art are demonstrated.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 10","pages":"2002-2014"},"PeriodicalIF":19.2,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145428898","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}
Jianguo Zhao;Linna Zhou;Weinan Gao;Hai Wang;Chunyu Yang
In this article, a novel model-free coordinated optimal regulation design methodology is proposed for the rigidly connected dual permanent magnet synchronous motor (PMSM) system via adaptive dynamic programming (ADP). First, we adopt the classical master-slave structure to maintain torque synchronization by virtue of field-oriented control. Then, a reduced-order model of the dual-PMSM system is established through the application of singular perturbation theory (SPT), which is of significance to decrease the learning time and computational complexity in the outer speed loop design. Afterwards, we design a coordinated adaptive optimal regulator in framework of ADP to drive the speed of girth gear asymptotic tracking the reference signal and accommodate the load torque disturbance, which is independent of the knowledge of model parameters of the system. According to SPT, we analyze the suboptimality, closedloop stability, and robustness properties of the obtained controller under mild conditions. Finally, comprehensive experimental studies are provided to verify that the proposed control strategy can achieve the speed regulation and the torque synchronization, as well as ameliorate the transient response.
{"title":"Model-Free Coordinated Optimal Regulation for Rigidly Connected Dual-PMSM Systems via Adaptive Dynamic Programming","authors":"Jianguo Zhao;Linna Zhou;Weinan Gao;Hai Wang;Chunyu Yang","doi":"10.1109/JAS.2025.125207","DOIUrl":"https://doi.org/10.1109/JAS.2025.125207","url":null,"abstract":"In this article, a novel model-free coordinated optimal regulation design methodology is proposed for the rigidly connected dual permanent magnet synchronous motor (PMSM) system via adaptive dynamic programming (ADP). First, we adopt the classical master-slave structure to maintain torque synchronization by virtue of field-oriented control. Then, a reduced-order model of the dual-PMSM system is established through the application of singular perturbation theory (SPT), which is of significance to decrease the learning time and computational complexity in the outer speed loop design. Afterwards, we design a coordinated adaptive optimal regulator in framework of ADP to drive the speed of girth gear asymptotic tracking the reference signal and accommodate the load torque disturbance, which is independent of the knowledge of model parameters of the system. According to SPT, we analyze the suboptimality, closedloop stability, and robustness properties of the obtained controller under mild conditions. Finally, comprehensive experimental studies are provided to verify that the proposed control strategy can achieve the speed regulation and the torque synchronization, as well as ameliorate the transient response.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 10","pages":"2138-2149"},"PeriodicalIF":19.2,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145428886","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}
Ying Zhang;Guohui Tian;Cuihua Zhang;Changchun Hua;Weili Ding;Choon Ki Ahn
Service robots are increasingly entering the home to provide domestic tasks for residents. However, when working in an open, dynamic, and unstructured home environment, service robots still face challenges such as low intelligence for task execution and poor long-term autonomy (LTA), which has limited their deployment. As the basis of robotic task execution, environment modeling has attracted significant attention. This integrates core technologies such as environment perception, understanding, and representation to accurately recognize environmental information. This paper presents a comprehensive survey of environmental modeling from a new task-execution-oriented perspective. In particular, guided by the requirements of robots in performing domestic service tasks in the home environment, we systematically review the progress that has been made in task-execution-oriented environmental modeling in four respects: 1) localization, 2) navigation, 3) manipulation, and 4) L T A. Current challenges are discussed, and potential research opportunities are also high-lighted.
服务机器人越来越多地进入家庭，为居民提供家务劳动。然而，当在开放、动态和非结构化的家庭环境中工作时，服务机器人仍然面临着诸如任务执行的低智能和较差的长期自主性（LTA）等挑战，这限制了它们的部署。环境建模作为机器人任务执行的基础，受到了广泛的关注。集成环境感知、理解、表征等核心技术，准确识别环境信息。本文从面向任务执行的新视角对环境建模进行了全面的综述。特别是，以机器人在家庭环境中执行家务服务任务的需求为指导，我们系统地回顾了面向任务执行的环境建模在四个方面取得的进展：1)定位，2)导航，3)操纵和4)L T a。
{"title":"Environment Modeling for Service Robots from a Task Execution Perspective","authors":"Ying Zhang;Guohui Tian;Cuihua Zhang;Changchun Hua;Weili Ding;Choon Ki Ahn","doi":"10.1109/JAS.2025.125168","DOIUrl":"https://doi.org/10.1109/JAS.2025.125168","url":null,"abstract":"Service robots are increasingly entering the home to provide domestic tasks for residents. However, when working in an open, dynamic, and unstructured home environment, service robots still face challenges such as low intelligence for task execution and poor long-term autonomy (LTA), which has limited their deployment. As the basis of robotic task execution, environment modeling has attracted significant attention. This integrates core technologies such as environment perception, understanding, and representation to accurately recognize environmental information. This paper presents a comprehensive survey of environmental modeling from a new task-execution-oriented perspective. In particular, guided by the requirements of robots in performing domestic service tasks in the home environment, we systematically review the progress that has been made in task-execution-oriented environmental modeling in four respects: 1) localization, 2) navigation, 3) manipulation, and 4) L T A. Current challenges are discussed, and potential research opportunities are also high-lighted.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 10","pages":"1985-2001"},"PeriodicalIF":19.2,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145428897","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}
Aiming at the pulse response sequence of a kind of repetitive linear discrete-time singular systems unavailable, the paper explores a data-driven adaptive iterative learning control (DDAILC) strategy that interacts with the pulse response iterative correction (PRIC). The mechanism is to formulate the correction performance index as a linear summation of the quadratic correction error of the pulse response and the quadratic tracking error. The correction algorithm of the pulse response arrives and the correction error goes down in a monotonic way. It also discusses the conditional relationship between the declining rate of the correction error and the correction ratio. A DDAILC algorithm is designed by means of substituting the exact pulse response of the gain-optimized iterative learning control (GOILC) with its approximated one updated in the correction algorithm. The convergences regarding tracking error and correction error are obtained monotonically. Finally, numerical simulation verifies the validity and effectiveness.
{"title":"Data-Driven Adaptive P-Type Iterative Learning Control for Linear Discrete Time Singular Systems","authors":"Ijaz Hussain;Xiaoe Ruan;Chuyang Liu;Bingqiang Li","doi":"10.1109/JAS.2024.125040","DOIUrl":"https://doi.org/10.1109/JAS.2024.125040","url":null,"abstract":"Aiming at the pulse response sequence of a kind of repetitive linear discrete-time singular systems unavailable, the paper explores a data-driven adaptive iterative learning control (DDAILC) strategy that interacts with the pulse response iterative correction (PRIC). The mechanism is to formulate the correction performance index as a linear summation of the quadratic correction error of the pulse response and the quadratic tracking error. The correction algorithm of the pulse response arrives and the correction error goes down in a monotonic way. It also discusses the conditional relationship between the declining rate of the correction error and the correction ratio. A DDAILC algorithm is designed by means of substituting the exact pulse response of the gain-optimized iterative learning control (GOILC) with its approximated one updated in the correction algorithm. The convergences regarding tracking error and correction error are obtained monotonically. Finally, numerical simulation verifies the validity and effectiveness.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 10","pages":"2067-2081"},"PeriodicalIF":19.2,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145428890","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}
In recent years, numerous recurrent neural network (RNN) models have been reported for solving time-dependent nonlinear optimization problems. However, few existing RNN models simultaneously involve nonlinear equality constraints, direct discretization, and noise suppression. This limitation presents challenges when existing models are applied to practical engineering problems. Additionally, most current discrete-time RNN models are derived from continuous-time models, which may not perform well for solving essentially discrete problems. To handle these issues, a robust direct-discretized RNN (RDD-RNN) model is proposed to efficiently realize time-dependent optimization constrained by nonlinear equalities (TDOCNE) in the presence of various time-dependent noises. Theoretical analyses are provided to reveal that the proposed RDD-RNN model possesses excellent convergence and noise-suppressing capability. Furthermore, numerical experiments and manipulator control instances are conducted and analyzed to validate the superior robustness of the proposed RDD-RNN model under various time-dependent noises, particularly quadratic polynomial noise. Eventually, small target detection experiments further demonstrate the practicality of the RDD-RNN model in image processing applications.
{"title":"A Robust Direct-Discretized RNN for Time-Dependent Optimization Constrained by Nonlinear Equalities and Its Applications","authors":"Guangfeng Cheng;Binbin Qiu;Jinjin Guo;Yu Han","doi":"10.1109/JAS.2025.125627","DOIUrl":"https://doi.org/10.1109/JAS.2025.125627","url":null,"abstract":"In recent years, numerous recurrent neural network (RNN) models have been reported for solving time-dependent nonlinear optimization problems. However, few existing RNN models simultaneously involve nonlinear equality constraints, direct discretization, and noise suppression. This limitation presents challenges when existing models are applied to practical engineering problems. Additionally, most current discrete-time RNN models are derived from continuous-time models, which may not perform well for solving essentially discrete problems. To handle these issues, a robust direct-discretized RNN (RDD-RNN) model is proposed to efficiently realize time-dependent optimization constrained by nonlinear equalities (TDOCNE) in the presence of various time-dependent noises. Theoretical analyses are provided to reveal that the proposed RDD-RNN model possesses excellent convergence and noise-suppressing capability. Furthermore, numerical experiments and manipulator control instances are conducted and analyzed to validate the superior robustness of the proposed RDD-RNN model under various time-dependent noises, particularly quadratic polynomial noise. Eventually, small target detection experiments further demonstrate the practicality of the RDD-RNN model in image processing applications.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 9","pages":"1866-1877"},"PeriodicalIF":19.2,"publicationDate":"2025-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335305","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}
Pedestrian trajectory prediction can significantly enhance the perception and decision-making capabilities of autonomous driving systems and intelligent surveillance systems based on camera sensors by predicting the states and behavior intentions of surrounding pedestrians. However, existing trajectory prediction methods remain failing to effectively model the diverse and complex interactions in the real world, including pedestrian-pedestrian interactions and pedestrian-environment interactions. Besides, these methods are not effective in capturing and characterizing the multimodal property of future trajectories. To address these challenges above, we propose to devise a hand-designed graph convolution and spatial cross attention to dynamically capture the diverse spatial interactions between pedestrians. To effectively explore the impact of scenarios on pedestrian trajectory, we build a pedestrian map, which can reflect the scene constraints and pedestrian motion preferences. Meanwhile, we construct a trajectory multimodality-aware module to capture the different potential mode implicit in diverse social behaviors for pedestrian future trajectory uncertainty. Finally, we compared the proposed method with trajectory prediction baselines on commonly used public pedestrian benchmarks, demonstrating the superior performance of our approach.
{"title":"Modelling Diverse Interactions and Multimodality for Pedestrian Trajectory Prediction","authors":"Ruiping Wang;Zhijian Hu;Junzhi Yu;Jun Cheng","doi":"10.1109/JAS.2025.125363","DOIUrl":"https://doi.org/10.1109/JAS.2025.125363","url":null,"abstract":"Pedestrian trajectory prediction can significantly enhance the perception and decision-making capabilities of autonomous driving systems and intelligent surveillance systems based on camera sensors by predicting the states and behavior intentions of surrounding pedestrians. However, existing trajectory prediction methods remain failing to effectively model the diverse and complex interactions in the real world, including pedestrian-pedestrian interactions and pedestrian-environment interactions. Besides, these methods are not effective in capturing and characterizing the multimodal property of future trajectories. To address these challenges above, we propose to devise a hand-designed graph convolution and spatial cross attention to dynamically capture the diverse spatial interactions between pedestrians. To effectively explore the impact of scenarios on pedestrian trajectory, we build a pedestrian map, which can reflect the scene constraints and pedestrian motion preferences. Meanwhile, we construct a trajectory multimodality-aware module to capture the different potential mode implicit in diverse social behaviors for pedestrian future trajectory uncertainty. Finally, we compared the proposed method with trajectory prediction baselines on commonly used public pedestrian benchmarks, demonstrating the superior performance of our approach.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 9","pages":"1801-1813"},"PeriodicalIF":19.2,"publicationDate":"2025-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335321","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}
Ming-Feng Ge;Yi-Fan Li;Chen-Bin Wu;Zhi-Wei Liu;Yan Jia;Si-Sheng Liu
Dear Editor, This letter investigates the problem of multi-dimension formation tracking (MDFT) for the cross-domain unmanned systems, including several interconnected agents, namely, unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs). We assume that each agent suffers from by the mixed constraints on its velocity, control input and Euler angle. Solving the MDFT problem implies that 1) The virtual state of each USV is determined in the earth coordinate by expanding its 2D work space to the 3D space; 2) The UAVs and the virtual states of the USVs form a user-defined geometric formation asymptotically in the 3D local coordinate; 3) The geometric center of the UAVs and the virtual states of the USVs tracks a reference trajectory asymptotically in the 3D earth coordinate. Therefore, a new hierarchical event-triggered predictive control (HETPC) algorithm is proposed to solve the MDFT problem, including the event-triggere cooperation layer and local 1ayer. The former solves the cooperative estimation problem of cross-domain systems with different dimensions, and the latter solves the trajectory tracking control problem under mixed constraints.
{"title":"Hierarchical Event-Triggered Predictive Control for Cross-Domain Unmanned Systems with Mixed Constraints","authors":"Ming-Feng Ge;Yi-Fan Li;Chen-Bin Wu;Zhi-Wei Liu;Yan Jia;Si-Sheng Liu","doi":"10.1109/JAS.2024.124797","DOIUrl":"https://doi.org/10.1109/JAS.2024.124797","url":null,"abstract":"Dear Editor, This letter investigates the problem of multi-dimension formation tracking (MDFT) for the cross-domain unmanned systems, including several interconnected agents, namely, unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs). We assume that each agent suffers from by the mixed constraints on its velocity, control input and Euler angle. Solving the MDFT problem implies that 1) The virtual state of each USV is determined in the earth coordinate by expanding its 2D work space to the 3D space; 2) The UAVs and the virtual states of the USVs form a user-defined geometric formation asymptotically in the 3D local coordinate; 3) The geometric center of the UAVs and the virtual states of the USVs tracks a reference trajectory asymptotically in the 3D earth coordinate. Therefore, a new hierarchical event-triggered predictive control (HETPC) algorithm is proposed to solve the MDFT problem, including the event-triggere cooperation layer and local 1ayer. The former solves the cooperative estimation problem of cross-domain systems with different dimensions, and the latter solves the trajectory tracking control problem under mixed constraints.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 9","pages":"1938-1940"},"PeriodicalIF":19.2,"publicationDate":"2025-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11208746","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335320","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}
Dear Editor, This letter is concerned with a coordinated path following control method for multiple unmanned underwater vehicles (UUVs) to carry out maritime search and rescue (MSR) missions. The kinetic model parameters of each UUV is totally unknown. Firstly, a kinematic control law is constructed by designing a vertical line-of-sight (LOS) guidance scheme. Secondly, a path variable update law is devised to realize careful MSR, which can achieve the coordinated control for networked UUVs. In addition, UUVs could stop at the predesigned MSR points automatically. Finally, a data-driven adaptive extended state observer (AESO) is proposed such that the unknown total disturbance, input gains and unmeasured velocities are simultaneously estimated without a prior kinetic model. The results are verified by numerical simulations for a fleet of UUVs to execute MSR.
{"title":"Adaptive Data-Driven Coordinated Control of UUVs for Maritime Search and Rescue","authors":"Hao-Liang Wang;De-Zhi Yu;Li-Yu Lu;Zhou-Hua Peng","doi":"10.1109/JAS.2024.124767","DOIUrl":"https://doi.org/10.1109/JAS.2024.124767","url":null,"abstract":"Dear Editor, This letter is concerned with a coordinated path following control method for multiple unmanned underwater vehicles (UUVs) to carry out maritime search and rescue (MSR) missions. The kinetic model parameters of each UUV is totally unknown. Firstly, a kinematic control law is constructed by designing a vertical line-of-sight (LOS) guidance scheme. Secondly, a path variable update law is devised to realize careful MSR, which can achieve the coordinated control for networked UUVs. In addition, UUVs could stop at the predesigned MSR points automatically. Finally, a data-driven adaptive extended state observer (AESO) is proposed such that the unknown total disturbance, input gains and unmeasured velocities are simultaneously estimated without a prior kinetic model. The results are verified by numerical simulations for a fleet of UUVs to execute MSR.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 9","pages":"1953-1955"},"PeriodicalIF":19.2,"publicationDate":"2025-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11208753","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335303","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}
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