The modeling and optimization of wind farm layouts can effectively reduce the wake effect between turbine units, thereby enhancing the expected output power and avoiding negative influence. Traditional wind farm optimization often uses idealized wake models, neglecting the influence of wind shear at different elevations, which leads to a lack of precision in estimating wake effects and fails to meet the accuracy and reliability requirements of practical engineering. To address this, we have constructed a three-dimensional 3D wind farm optimization model that incorporates elevation, utilizing a 3D wake model to better reflect real-world conditions. We aim to assess the optimization state of the algorithm and provide strong incentives at the right moments to ensure continuous evolution of the population. To this end, we propose an evolutionary adaptation degree-guided genetic algorithm based on power-law perturbation (PPGA) to adapt multidimensional conditions. We select the offshore wind power project in Nantong, Jiangsu, China, as a study example and compare PPGA with other well-performing algorithms under this practical project. Based on the actual wind condition data, the experimental results demonstrate that PPGA can effectively tackle this complex problem and achieve the best power efficiency.
{"title":"Advanced 3D Wind Farm Layout Optimization Framework via Power-Law Perturbation-Based Genetic Algorithm","authors":"Jiaru Yang;Yaotong Song;Jun Tang;Weiping Ding;Zhenyu Lei;Shangce Gao","doi":"10.1109/JAS.2025.125351","DOIUrl":"https://doi.org/10.1109/JAS.2025.125351","url":null,"abstract":"The modeling and optimization of wind farm layouts can effectively reduce the wake effect between turbine units, thereby enhancing the expected output power and avoiding negative influence. Traditional wind farm optimization often uses idealized wake models, neglecting the influence of wind shear at different elevations, which leads to a lack of precision in estimating wake effects and fails to meet the accuracy and reliability requirements of practical engineering. To address this, we have constructed a three-dimensional 3D wind farm optimization model that incorporates elevation, utilizing a 3D wake model to better reflect real-world conditions. We aim to assess the optimization state of the algorithm and provide strong incentives at the right moments to ensure continuous evolution of the population. To this end, we propose an evolutionary adaptation degree-guided genetic algorithm based on power-law perturbation (PPGA) to adapt multidimensional conditions. We select the offshore wind power project in Nantong, Jiangsu, China, as a study example and compare PPGA with other well-performing algorithms under this practical project. Based on the actual wind condition data, the experimental results demonstrate that PPGA can effectively tackle this complex problem and achieve the best power efficiency.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 11","pages":"2314-2328"},"PeriodicalIF":19.2,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145674880","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}
Robot interaction control with variable impedance parameters may conform to task requirements during continuous interaction with dynamic environments. Iterative learning (IL) is effective to learn desired impedance parameters for robots under unknown environments, and Gaussian process (GP) is a nonparametric Bayesian approach that models complicated functions with provable confidence using limited data. In this paper, we propose an impedance IL method enhanced by a sparse online Gaussian process (SOGP) to speed up learning convergence and improve generalization. The SOGP for variable impedance modeling is updated in the same iteration by removing similar data points from previous iterations while learning impedance parameters in multiple iterations. The proposed IL-SOGP method is verified by high-fidelity simulations of a collaborative robot with 7 degrees of freedom based on the admittance control framework. It is shown that the proposed method accelerates iterative convergence and improves generalization compared to the classical IL-based impedance learning method.
{"title":"Robot Impedance Iterative Learning with Sparse Online Gaussian Process","authors":"Yongping Pan;Tian Shi;Wei Li;Bin Xu;Choon Ki Ahn","doi":"10.1109/JAS.2025.125195","DOIUrl":"https://doi.org/10.1109/JAS.2025.125195","url":null,"abstract":"Robot interaction control with variable impedance parameters may conform to task requirements during continuous interaction with dynamic environments. Iterative learning (IL) is effective to learn desired impedance parameters for robots under unknown environments, and Gaussian process (GP) is a nonparametric Bayesian approach that models complicated functions with provable confidence using limited data. In this paper, we propose an impedance IL method enhanced by a sparse online Gaussian process (SOGP) to speed up learning convergence and improve generalization. The SOGP for variable impedance modeling is updated in the same iteration by removing similar data points from previous iterations while learning impedance parameters in multiple iterations. The proposed IL-SOGP method is verified by high-fidelity simulations of a collaborative robot with 7 degrees of freedom based on the admittance control framework. It is shown that the proposed method accelerates iterative convergence and improves generalization compared to the classical IL-based impedance learning method.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 11","pages":"2218-2227"},"PeriodicalIF":19.2,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145674873","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}
Both evolutionary computation (EC) and multi-agent systems (MAS) study the emergence of intelligence through the interaction and cooperation of a group of individuals. EC focuses on solving various complex optimization problems, while MAS provides a flexible model for distributed artificial intelligence. Since their group interaction mechanisms can be borrowed from each other, many studies have attempted to combine EC and MAS. With the rapid development of the Internet of Things, the confluence of EC and MAS has become more and more important, and related articles have shown a continuously growing trend during the last decades. In this survey, we first elaborate on the mutual assistance of EC and MAS from two aspects, agent-based EC and EC-assisted MAS. Agent-based EC aims to introduce characteristics of MAS into EC to improve the performance and parallelism of EC, while EC-assisted MAS aims to use EC to better solve optimization problems in MAS. Furthermore, we review studies that combine the cooperation mechanisms of EC and MAS, which greatly leverage the strengths of both sides. A description framework is built to elaborate existing studies. Promising future research directions are also discussed in conjunction with emerging technologies and real-world applications.
{"title":"The Confluence of Evolutionary Computation and Multi-Agent Systems: A Survey","authors":"Tai-You Chen;Wei-Neng Chen;Feng-Feng Wei;Xiao-Qi Guo;Wen-Xiang Song;Rui Zhu;Qiuzhen Lin;Jun Zhang","doi":"10.1109/JAS.2025.125246","DOIUrl":"https://doi.org/10.1109/JAS.2025.125246","url":null,"abstract":"Both evolutionary computation (EC) and multi-agent systems (MAS) study the emergence of intelligence through the interaction and cooperation of a group of individuals. EC focuses on solving various complex optimization problems, while MAS provides a flexible model for distributed artificial intelligence. Since their group interaction mechanisms can be borrowed from each other, many studies have attempted to combine EC and MAS. With the rapid development of the Internet of Things, the confluence of EC and MAS has become more and more important, and related articles have shown a continuously growing trend during the last decades. In this survey, we first elaborate on the mutual assistance of EC and MAS from two aspects, agent-based EC and EC-assisted MAS. Agent-based EC aims to introduce characteristics of MAS into EC to improve the performance and parallelism of EC, while EC-assisted MAS aims to use EC to better solve optimization problems in MAS. Furthermore, we review studies that combine the cooperation mechanisms of EC and MAS, which greatly leverage the strengths of both sides. A description framework is built to elaborate existing studies. Promising future research directions are also discussed in conjunction with emerging technologies and real-world applications.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 11","pages":"2175-2193"},"PeriodicalIF":19.2,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145674845","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}
Jiahao Zhu;Shujin Yuan;Lisheng Mou;Jun Luo;Huayan Pu
Unknown time-varying periodic disturbances and input delays can degrade control performance and even lead to system instability. This paper presents a novel direct adaptive output feedback controller based on the internal model principle (IMP) to compensate for the unknown time-varying periodic disturbance in input delay systems. To reduce the design difficulty of the controller, the input delay system is equivalent to an input delay-free system by constructing stable auxiliary systems. Next, all the stabilizing controllers of the input delay system are derived by using the Youla parameterization method. Based on the IMP, an interpolation condition to completely compensate for periodic disturbances is formulated. Then, to compensate for the unknown time-varying periodic disturbance, a parameter adaptive algorithm is designed to update the Q-parameters online. The convergence of adaptive algorithms is analyzed by the Lyapunov function theory. Simulation and experimental results validated the effectiveness of the proposed method.
{"title":"Adaptive Periodic Disturbance Compensation for Continuous-Time Linear Systems with Input Delays","authors":"Jiahao Zhu;Shujin Yuan;Lisheng Mou;Jun Luo;Huayan Pu","doi":"10.1109/JAS.2025.125258","DOIUrl":"https://doi.org/10.1109/JAS.2025.125258","url":null,"abstract":"Unknown time-varying periodic disturbances and input delays can degrade control performance and even lead to system instability. This paper presents a novel direct adaptive output feedback controller based on the internal model principle (IMP) to compensate for the unknown time-varying periodic disturbance in input delay systems. To reduce the design difficulty of the controller, the input delay system is equivalent to an input delay-free system by constructing stable auxiliary systems. Next, all the stabilizing controllers of the input delay system are derived by using the Youla parameterization method. Based on the IMP, an interpolation condition to completely compensate for periodic disturbances is formulated. Then, to compensate for the unknown time-varying periodic disturbance, a parameter adaptive algorithm is designed to update the Q-parameters online. The convergence of adaptive algorithms is analyzed by the Lyapunov function theory. Simulation and experimental results validated the effectiveness of the proposed method.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 11","pages":"2286-2299"},"PeriodicalIF":19.2,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145674729","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}
Dear Editor, This letter addresses distributed optimization for resource allocation problems with time-varying objective functions and time-varying constraints. Inspired by the distributed average tracking (DAT) approach, a distributed control protocol is proposed for optimal resource allocation. The convergence to a time-varying optimal solution within a predefined time is proved. Two numerical examples are given to illustrate the effectiveness of the proposed approach.
{"title":"Predefined-Time Distributed Optimization for Resource Allocation Problems with Time-Varying Objective Function and Constraints","authors":"Haotian Wu;Yang Liu;Mahmoud Abdel-Aty;Weihua Gui","doi":"10.1109/JAS.2024.124992","DOIUrl":"https://doi.org/10.1109/JAS.2024.124992","url":null,"abstract":"Dear Editor, This letter addresses distributed optimization for resource allocation problems with time-varying objective functions and time-varying constraints. Inspired by the distributed average tracking (DAT) approach, a distributed control protocol is proposed for optimal resource allocation. The convergence to a time-varying optimal solution within a predefined time is proved. Two numerical examples are given to illustrate the effectiveness of the proposed approach.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 11","pages":"2353-2355"},"PeriodicalIF":19.2,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11271414","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145674728","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}
It is a challenging issue to obtain the minimum amplitude control for linear systems subject to amplitude-bounded disturbances. The difficulty is how to accurately give the quantitative relationship between the system ${H}_{infty}$ norm and control parameters. An optimal-Lyapunov-function-based controller design concept is proposed, and a minimum amplitude control scheme is presented under amplitude-bounded disturbances. Firstly, the optimal Lyapunov function is proposed by analyzing the geometric characteristics of the system ${H}_{infty}$ norm, and the necessary and sufficient condition of the optimal Lyapunov function parameter matrix is given. Secondly, the optimal Lyapunov function parameter matrix is constructed in the parameterized matrix equation, and the accurate quantitative relationship between the system ${H}_{infty}$ norm and control parameters is given. Finally, the control parameter optimization method is proposed according to the quantitative relationship between the system ${H}_{infty}$ norm and control parameters. Unlike robust optimization control methods, the presented minimum amplitude control scheme avoids the improper selection of the Lyapunov function in the controller design, and provides a novel way to design the minimum amplitude control under the given control accuracy. A buck converter example is given to illustrate the effectiveness and practicability of the presented scheme.
{"title":"Optimal Lyapunov Function and Minimum Amplitude Control for Disturbed Linear Systems","authors":"Xiuchong Liu;Zhanshan Wang","doi":"10.1109/JAS.2025.125252","DOIUrl":"https://doi.org/10.1109/JAS.2025.125252","url":null,"abstract":"It is a challenging issue to obtain the minimum amplitude control for linear systems subject to amplitude-bounded disturbances. The difficulty is how to accurately give the quantitative relationship between the system <tex>${H}_{infty}$</tex> norm and control parameters. An optimal-Lyapunov-function-based controller design concept is proposed, and a minimum amplitude control scheme is presented under amplitude-bounded disturbances. Firstly, the optimal Lyapunov function is proposed by analyzing the geometric characteristics of the system <tex>${H}_{infty}$</tex> norm, and the necessary and sufficient condition of the optimal Lyapunov function parameter matrix is given. Secondly, the optimal Lyapunov function parameter matrix is constructed in the parameterized matrix equation, and the accurate quantitative relationship between the system <tex>${H}_{infty}$</tex> norm and control parameters is given. Finally, the control parameter optimization method is proposed according to the quantitative relationship between the system <tex>${H}_{infty}$</tex> norm and control parameters. Unlike robust optimization control methods, the presented minimum amplitude control scheme avoids the improper selection of the Lyapunov function in the controller design, and provides a novel way to design the minimum amplitude control under the given control accuracy. A buck converter example is given to illustrate the effectiveness and practicability of the presented scheme.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 11","pages":"2264-2274"},"PeriodicalIF":19.2,"publicationDate":"2025-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145612076","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}
Considering that actual systems are often constrained by multiple factors such as state limitation, actuator saturation and actuator failure at the same time, this paper provides an effective solution for non-affine multi-player systems, which can guarantee the required performance while saving communication cost. Initially, an auxiliary system is established to accommodate state limitations, following which the controller design is partitioned into two distinct segments, addressing different types of faults. Specifically, the discontinuous and continuous aspects of the controller are achieved by sliding-mode control (SMC) and adaptive critic design (ACD), respectively. During the implementation of ACD to solve the guaranteed value function incorporating the utility function designed for the asymmetric saturation of the control input, two adaptive schemes including adaptive event-triggered impulsive control (AETIC) and adaptive self-triggered impulsive control (ASTIC) are introduced successively. It is proved that the system maintains exponential stability rather than asymptotic stability and the state signals keep ultimately uniformly bounded (UUB). Finally, the effectiveness of the proposed control sequence is verified by simulation comparisons.
{"title":"Adaptive Self-Triggered Impulsive Fault-Tolerant Control for Multi-Player Constrained Systems","authors":"Lu Liu;Ruizhuo Song;Lina Xia","doi":"10.1109/JAS.2025.125288","DOIUrl":"https://doi.org/10.1109/JAS.2025.125288","url":null,"abstract":"Considering that actual systems are often constrained by multiple factors such as state limitation, actuator saturation and actuator failure at the same time, this paper provides an effective solution for non-affine multi-player systems, which can guarantee the required performance while saving communication cost. Initially, an auxiliary system is established to accommodate state limitations, following which the controller design is partitioned into two distinct segments, addressing different types of faults. Specifically, the discontinuous and continuous aspects of the controller are achieved by sliding-mode control (SMC) and adaptive critic design (ACD), respectively. During the implementation of ACD to solve the guaranteed value function incorporating the utility function designed for the asymmetric saturation of the control input, two adaptive schemes including adaptive event-triggered impulsive control (AETIC) and adaptive self-triggered impulsive control (ASTIC) are introduced successively. It is proved that the system maintains exponential stability rather than asymptotic stability and the state signals keep ultimately uniformly bounded (UUB). Finally, the effectiveness of the proposed control sequence is verified by simulation comparisons.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 11","pages":"2228-2238"},"PeriodicalIF":19.2,"publicationDate":"2025-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145612092","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}
Xu Wang;Yi Jin;Hui Yu;Yigang Cen;Tao Wang;Yidong Li
Task-oriented point cloud sampling aims to select a representative subset from the input, tailored to specific application scenarios and task requirements. However, existing approaches rarely tackle the problem of redundancy caused by local structural similarities in 3D objects, which limits the performance of sampling. To address this issue, this paper introduces a novel task-oriented point cloud masked autoencoder-based sampling network (Point-MASNet), inspired by the masked autoencoder mechanism. Point-MASNet employs a voxel-based random non-overlapping masking strategy, which allows the model to selectively learn and capture distinctive local structural features from the input data. This approach effectively mitigates redundancy and enhances the representativeness of the sampled subset. In addition, we propose a lightweight, symmetrically structured keypoint reconstruction network, designed as an autoencoder. This network is optimized to efficiently extract latent features while enabling refined reconstructions. Extensive experiments demonstrate that Point-MASNet achieves competitive sampling performance across classification, registration, and reconstruction tasks.
{"title":"Point-MASNet: Masked Autoencoder-Based Sampling Network for 3D Point Cloud","authors":"Xu Wang;Yi Jin;Hui Yu;Yigang Cen;Tao Wang;Yidong Li","doi":"10.1109/JAS.2024.125088","DOIUrl":"https://doi.org/10.1109/JAS.2024.125088","url":null,"abstract":"Task-oriented point cloud sampling aims to select a representative subset from the input, tailored to specific application scenarios and task requirements. However, existing approaches rarely tackle the problem of redundancy caused by local structural similarities in 3D objects, which limits the performance of sampling. To address this issue, this paper introduces a novel task-oriented point cloud masked autoencoder-based sampling network (Point-MASNet), inspired by the masked autoencoder mechanism. Point-MASNet employs a voxel-based random non-overlapping masking strategy, which allows the model to selectively learn and capture distinctive local structural features from the input data. This approach effectively mitigates redundancy and enhances the representativeness of the sampled subset. In addition, we propose a lightweight, symmetrically structured keypoint reconstruction network, designed as an autoencoder. This network is optimized to efficiently extract latent features while enabling refined reconstructions. Extensive experiments demonstrate that Point-MASNet achieves competitive sampling performance across classification, registration, and reconstruction tasks.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 11","pages":"2300-2313"},"PeriodicalIF":19.2,"publicationDate":"2025-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145612155","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}
Laura Lucantoni;Stefano Croci;Giovanni Mazzuto;Filippo Emanuele Ciarapica;Maurizio Bevilacqua;Severino Perenzoni
Dear Editor, The food industry emphasizes improving demand forecasting to align production with consumer needs and reduce waste. This letter thus presents a study that integrates artificial intelligence (AI) and digital twin (DT) technologies to enhance decision-making and efficiency in food production. A data-driven DT was implemented in an Italian company for Raspberry production planning, based on a daily demand forecasting tool powered by a dynamic extreme gradient boosting (XGBoost) algorithm. The model achieved a mean absolute percentage error (MAPE) of 16.37% with 1.69 average of absolute extra working hours (AEW) and a tracking signal (TS) range of [−1.9, +4.3].
{"title":"Demand Forecasting Tool Driving the Digital Twin of a Perishable Food Process","authors":"Laura Lucantoni;Stefano Croci;Giovanni Mazzuto;Filippo Emanuele Ciarapica;Maurizio Bevilacqua;Severino Perenzoni","doi":"10.1109/JAS.2025.125591","DOIUrl":"https://doi.org/10.1109/JAS.2025.125591","url":null,"abstract":"Dear Editor, The food industry emphasizes improving demand forecasting to align production with consumer needs and reduce waste. This letter thus presents a study that integrates artificial intelligence (AI) and digital twin (DT) technologies to enhance decision-making and efficiency in food production. A data-driven DT was implemented in an Italian company for Raspberry production planning, based on a daily demand forecasting tool powered by a dynamic extreme gradient boosting (XGBoost) algorithm. The model achieved a mean absolute percentage error (MAPE) of 16.37% with 1.69 average of absolute extra working hours (AEW) and a tracking signal (TS) range of [−1.9, +4.3].","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 11","pages":"2356-2358"},"PeriodicalIF":19.2,"publicationDate":"2025-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11271418","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145612175","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}
Yiming Li;Xiao Wang;Jinglong Shi;Jian Liu;Changyin Sun
This paper investigates the modeling and the practical predefined-time (PdT) tracking control problems for a fully actuated disk-shaped autonomous underwater vehicle (AUV) with six degrees of freedom. To overcome the gimbal lock problem inherent in Euler angle representation, unit quaternions are adopted to model the AUV, accounting for internal uncertainties and external disturbances. Then, an improved time-varying function is introduced, which serves as the basis for designing a non-singular sliding surface and sliding mode controller with PdT stability. This approach ensures that the tracking errors converge within a predefined time, independent of initial conditions and design parameters. Compared with traditional PdT controllers, the proposed method eliminates singularities, enhances the precision of convergence time estimation, and typically yields smaller, smoother initial control inputs, thus improving its potential for engineering applications. Numerical simulations validate the effectiveness and performance of the proposed controller.
{"title":"Quaternion-Based Modeling and Predefined-Time Tracking Control of a Fully Actuated Autonomous Underwater Vehicle","authors":"Yiming Li;Xiao Wang;Jinglong Shi;Jian Liu;Changyin Sun","doi":"10.1109/JAS.2025.125267","DOIUrl":"https://doi.org/10.1109/JAS.2025.125267","url":null,"abstract":"This paper investigates the modeling and the practical predefined-time (PdT) tracking control problems for a fully actuated disk-shaped autonomous underwater vehicle (AUV) with six degrees of freedom. To overcome the gimbal lock problem inherent in Euler angle representation, unit quaternions are adopted to model the AUV, accounting for internal uncertainties and external disturbances. Then, an improved time-varying function is introduced, which serves as the basis for designing a non-singular sliding surface and sliding mode controller with PdT stability. This approach ensures that the tracking errors converge within a predefined time, independent of initial conditions and design parameters. Compared with traditional PdT controllers, the proposed method eliminates singularities, enhances the precision of convergence time estimation, and typically yields smaller, smoother initial control inputs, thus improving its potential for engineering applications. Numerical simulations validate the effectiveness and performance of the proposed controller.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 11","pages":"2275-2285"},"PeriodicalIF":19.2,"publicationDate":"2025-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145612130","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}
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