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Neural Network for Distributed Collaboration of Multiple Manipulators With Switching Topologies: A Game-Theoretic Perspective

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3213-3221页

作者： Liu, Mei Mu, Wenxin Lv, Xin Sun, Zhongbo Jin, Long Lanzhou University School of Information Science and Engineering Lanzhou730000 China Changchun University of Technology Department of Control Engineering Changchun130000 China

Since distributed control strategies can effectively reduce the operating load of the central processor, they have become a prominent research direction in the field of controlling multiple manipulators. However, existing distributed approaches predominantly rely on fixed topologies, overlooking the dynamic nature of task requirements. To address this limitation, this article proposes a distributed collaboration scheme that incorporates switching topologies. The distributed control problem is further formulated as a game-theoretic framework involving multiple manipulators. A dynamic neural network solver is then developed to approximate the optimal Nash equilibrium strategy, with its convergence and stability proven through theoretical analysis. The effectiveness of the proposed scheme and solver is validated through a series of physical experiments. © 2013 IEEE.

关键词： Redundant manipulators

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Enhanced Tube-Based Event-Triggered Stochastic Model Predictive control With Additive Uncertainties

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 596-605页

作者： Chenxi Gu Xinli Wang Kang Li Xiaohong Yin Shaoyuan Li Lei Wang the School of Control Science and Engineering Shandong University IEEE the School of Electronic and Electrical Engineering University of Leeds the Qingdao University of Science and Technology the Department of Automation Shanghai Jiao Tong University the Key Laboratory of System Control and Information Processing Ministry of Education of China

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 *** 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.

关键词： Event-triggered mechanism heating, ventilation, and air conditioning (HVAC) control probabilistic reachable set stochastic model predictive control

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Data-driven output regulation control for constrained linear systems

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Science China(information Sciences) 2025年第3期68卷 338-353页

作者： Chaoyu XIA Yi DONG Chaoli WANG Shengyuan XU Shanghai Research Institute for Intelligent Autonomous Systems Tongji University College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous SystemsTongji University Department of Control Science and Engineering School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and Technology Department of Automation Nanjing University of Science and Technology

This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking performance while satisfying the state and input constraints, even when system matrices are not available. We first establish a sufficient condition necessary for the existence of a solution pair to the regulator equation and propose a data-based approach to obtain the feedforward and feedback control gains for state feedback control using linear programming. Furthermore, we design a refined Luenberger observer to accurately estimate the system state, while keeping the estimation error within a predefined set. By combining output regulation theory, we develop an output feedback control strategy. The stability of the closed-loop system is rigorously proved to be asymptotically stable by further leveraging the concept of λ-contractive sets.

关键词： output regulation constrained system data-driven.

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controllability of heterogeneous networked sampled-data systems

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Science China(information Sciences) 2025年第3期68卷 302-318页

作者： Zixuan YANG Lin WANG Xiaofan WANG Guanrong CHEN Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China School of Mechatronic Engineering and Automation Shanghai University School of Electrical and Electronic Engineering Shanghai Institute of Technology Department of Electrical Engineering City University of Hong Kong

This study investigates the controllability of a general heterogeneous networked sampled-data system(HNSS) consisting of nonidentical node systems, where the inner coupling between any pair of nodes can be described by a unique *** signals on control and transmission channels are sampled and held by zero-order holders, and the control sampling period of each node can be different. Necessary and sufficient controllability conditions are developed for the general HNSS, using the Smith normal form and matrix equations, respectively. The HNSS in specific topology or dynamic settings is discussed subsequently with easier-to-verify conditions derived. These heterogeneous factors have been determined to independently or jointly affect the controllability of networked sampled-data systems. Notably, heterogeneous sampling periods have the potential to enhance the overall controllability, but not for systems with some special dynamics. When the node dynamics are heterogeneous,the overall system can be controllable even if it is topologically uncontrollable. In addition, in several typical heterogeneous sampled-data multi-agent systems, pathological sampling of single-node systems will necessarily cause overall uncontrollability.

关键词： network controllability sampled-data system heterogeneous system inner coupling multi-agent system

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Internet information Intelligent Recommendation System Under Deep Learning and Big Data

Internet Information Intelligent Recommendation System Under...

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作者： Yan, Kai Gao, Hao Department of Information and Control Engineering Shenyang Institute of Science and Technology Liaoning Shenyang110000 China

The explosive growth of information on the internet poses great challenges to users. In response to the above issues, this article studies the construction of an intelligent recommendation system for internet information using a combination of deep learning and big data methods. This article adopts deep learning methods to model user behavior data and combines big data analysis to provide personalized recommendation services for users. This article compared the information recommendation accuracy of two other intelligent recommendation systems through experiments. The system designed in this article achieved an accuracy of 92.5% in this regard, far superior to the other two. Experimental results have shown that the system designed in this article not only improves recommendation accuracy, but also enhances user satisfaction. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Data accuracy

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YOLOv8n-CGW: A novel approach to multi-oriented vehicle detection in intelligent transportation systems

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Multimedia Tools and Applications 2025年第7期84卷 3809-3840页

作者： Berwo, Michael Abebe Fang, Yong Sarwar, Nadeem Mahmood, Jabar Aljohani, Mansourah Elhosseini, Mostafa School of Information and Engineering Chang’an University Shaanxi Xi’an710064 China Department of Computer Science Bahria University Lahore Campus Punjab Lahore54600 Pakistan Department of Information Technology Faculty of Computing and Information Technology University of Sialkot Punjab Sialkot51040 Pakistan College of Computer Science and Engineering Taibah University Yanbu46421 Saudi Arabia Computers and Control Systems Engineering Department Faculty of Engineering Mansoura University Mansoura35516 Egypt

In the context of Intelligent Transportation Systems (ITS), the role of vehicle detection and classification is indispensable for streamlining transportation management, refining traffic control, and conducting in-depth accident analyses. However, the intricate task of accurately detecting multi-oriented vehicles in diverse scenarios remains a challenge, even with the advancements in ITS. Factors such as vehicle morphology, design, road conditions, structural details, and climatic variables provide a significant part in the detection. To address this, our study introduces an advanced YOLOv8n model, specifically the YOLOv8n-CGW, which is built upon pre-trained deep learning frameworks. This model is meticulously tailored to enhance the detection capabilities for multi-oriented vehicles. Comprehensive evaluations on esteemed datasets like MtV, MERGED, Custom dataset, DAWN, WEDGE, and UA-DETRAC underscore the superiority of our approach over existing models. Notably, our YOLOv8n-CGW model achieves a remarkable mAP of 83.3% and boasts a swift inference time of 0.0019s, setting a new benchmark in the domain. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Deep neural networks

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Formation control Design of Fixed-wing UAVs Based on Model Reference Adaptive control

Periodica Polytechnica Electrical Engineering and Computer S...

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Periodica Polytechnica Electrical engineering and Computer Science 2025年第1期69卷 43-52页

作者： Lantos, Bela Kimathi, Stephen Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Műegyetem rkp. 3. BudapestH-1111 Hungary Department of Electrical and Electronic Engineering Dedan Kimathi University of Technology P.O.B. 10143 Dedan Kimathi Nyeri10100 Kenya

Formation control is currently a popular field of research due to the increasing application areas of unmanned aerial vehicles. Of concern is the stability of unmanned aerial vehicles (UAVs) formation while tracking especially under the influence of disturbances, and model parameter uncertainty. Since formation of the UAV formation while tracking, especially flying involves a mutual cooperation, consensus-based techniques are more suited such that a group of UAVs are collectively coordinated to perform some tasks. In this paper, a leader–follower formation control of homogeneous fixed wing UAVs based on model reference adaptive control with an integral error control compensation is presented. Model reference adaptive control is powerful and effective for handling uncertain and varying dynamics. This proposed distributed composite control strategy with a directed graph topology, although model-dependent can be effective to suppress disturbances affecting the vehicles, while achieving consensus-based tracking of a reference path. The numerical simulation results given show the applicability of this proposed control strategy. © 2025 Budapest University of technology and Economics. All rights reserved.

关键词： Directed graphs

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Sliding mode active disturbance rejection control for uncalibrated visual servoing

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International Journal of Systems, control and Communications 2025年第2期16卷 133-151页

作者： Pu, Cuiping Wu, Yi Ren, Jie Ran, Chenyang College of Mechanical and Electrical Engineering Kunming University Kunming China School of Information and Control Engineering China University of Mining and Technology Xuzhou China Department of Automation Shanghai Jiao Tong University Shanghai China

A sliding mode control algorithm based on a linear extended state observer is proposed to address the multi-source uncertainty of uncalibrated visual servoing in robotic arms. Uncertainty, nonlinearity, coupling, external disturbances, etc. are considered as total disturbances. The linear expansion state observer is designed to observe the total disturbance and compensate for it. This enhances the system’s anti-interference ability. The outer loop adopts sliding mode control law as state feedback. It suppresses the observation errors of the observer and ensures the stability of the system. Sliding mode control based on linear extended observer does not depend on specific tasks and system configurations. It provides a unified design framework for solving the problem of uncalibrated visual servoing. Through numerical simulations of three different disturbance cases, it was compared with PI linear extended state observer and linear active disturbance rejection to verify its good dynamic performance and disturbance rejection performance. Copyright © 2025 Inderscience Enterprises Ltd.

关键词： Robotic arms

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Robust Adaptive Sliding Mode Security control of Markov Jump Cyber-Physical Systems With Stochastic Injection Attacks Through Event-Triggered-Based Observer Approach

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3679-3692页

作者： Jiang, Baoping Niu, Fuzhou Wu, Zhengtian Qiu, Jianbin Suzhou University of Science and Technology School of Electronic and Information Engineering Suzhou215009 China Politecnico di Milano Department of Mechanical Engineering Milan20156 Italy Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin150001 China

This article addresses the challenge of state observer design for sliding mode security control in Markov jump cyber-physical systems subjected to stochastic injection attacks. To enhance network efficiency, a dynamic event-triggered algorithm is introduced in the communication channel. First, the design begins with a Luenberger state observer featuring an adaptive compensator. This configuration aims to effectively counteract malicious attacks. Second, an integral sliding hyperplane is formulated within the estimation space, which serves as the foundation for deriving the sliding mode dynamics, ensuring robustness against disturbances. Recognizing the diversity of transition rates (TRs), an elastic sliding mode controller is designed to accommodate three distinct types of TRs, which is also strategically designed to guarantee reachability and maintain sliding motion. Third, stochastic stability with an H∞ attenuation level is conducted separately for each type of TR. Correspondingly, the development of an algorithm for determining threshold parameters in triggered conditions is presented. Simultaneously, a proof of the nonexistence of Zeno behavior is provided, ensuring the stability and efficiency of the proposed system. Finally, a simulation study using a practical model is included to empirically demonstrate the validity of the proposed method in a real-world context. © 2013 IEEE.

关键词： Stochastic systems

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Dynamic Modeling and control for an Offshore Semisubmersible Floating Wind Turbine

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IEEE Transactions on Automation Science and engineering 2025年 22卷 12371-12382页

作者： Gong, Yingjie Yang, Qinmin Geng, Hua Meng, Wenchao Wang, Lin Zhejiang University State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Hangzhou310027 China Huzhou Institute Zhejiang University State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Hangzhou310027 China Tsinghua University Beijing National Research Center for Information Science and Technology Department of Automation Beijing100084 China Zhejiang Windey Company Ltd. Hangzhou310027 China

Floating wind turbines (FWTs) hold significant potential for the exploitation of offshore renewable energy resources. Nevertheless, prior to the construction of FWTs, it is imperative to tackle several critical challenges, especially the issue of performance degradation under combined wind and wave loads. This study initiates with the development of a simplified nonlinear dynamical model for a semi-submersible FWT. In particular, both the rotor dynamics and the finite rotations of the platform are considered in presented modeling approach, thereby effectively capturing the complex interplay between the platform, tower, nacelle, and rotor under combined wind and wave loads. Subsequently, based on the developed FWT model, a novel adaptive nonlinear pitch controller is formulated with the goal of striking a trade-off between regulating power generation and reducing platform motion. Notably, the proposed control strategy adopts a continuous control approach, strategically beneficial in circumventing the chattering phenomenon commonly associated with sliding mode control. Furthermore, the controller integrates an online approximator and a robust integral of the sign of the tracking error, facilitating real-time learning of system unknown dynamics while compensating for bounded disturbances. Finally, both the accuracy of the established nonlinear FWT model in predicting key dynamics and the superiority of the presented pitch controller are validated through comprehensive comparative studies. Note to Practitioners - This paper addresses the conflicting goals between power regulation and load mitigation for floating wind turbines (FWTs) to ensure the reliable operation of wind turbine systems. This remains an ongoing challenge due to the inherent complexity of existing FWT models, frequently resulting in controllers crafted using linearized representations that fail to accommodate real-world uncertainties effectively. Through the utilization of a simplified physical-based n

关键词： Renewable energy

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