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检索条件"机构=School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems"

共 2865 条记录，以下是921-930 订阅

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Fixed-Time Sliding Mode Tracking control for Two-Dimensional Directional Drilling System

Fixed-Time Sliding Mode Tracking Control for Two-Dimensional...

引用

Asian control Conference

作者： Jinyu Li Hongchao Wei Chengda Lu Wangnian Li Quanxin Li Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Xi'an Research Institute Co. Ltd. China Coal Technology and Engineering Group Xi'an China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

In this paper, the effect of the initial state of the drilling system on trajectory tracking is taken into account in the directional drilling trajectory tracking control. Firstly, the trajectory model describing the two-dimensional drilling trajectory of the rotary steering system (RSS) is introduced. To improve the accuracy of trajectory tracking control and reduce the trajectory deviation, a fixed-time sliding mode control (FTSMC) method is introduced. Then, the stability of the closed-loop system is analyzed, and the range of controller parameters satisfying the stability condition is obtained. Finally, the effectiveness of the designed control strategy is verified by simulation experiments.

关键词： Drilling Upper bound Trajectory tracking Steering systems Stability analysis Trajectory Closed loop systems

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Fog Images Generation about Unmanned Surface Vessels with Improved Generative Adversarial Network

Fog Images Generation about Unmanned Surface Vessels with Im...

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第42届中国控制会议

作者： Yifeng Tang Zhihui Huang Chuancong Tang Chuanshang Luo Yifan Xu Bin Liu Hai-Tao Zhang School of Artificial Intelligence and Automation the Engineering Research Center of Autonomous Intelligent Unmanned Systems the Key Laboratory of Image Processing and Intelligent Control and the State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology

This paper proposes a fog weather data augmentation method for the unmanned surface vessels(USVs) via improved Generative Adversarial Network(GAN) model. First, a generator scheme for GAN is proposed with the guided generation of the atmospheric scattering model in this paper. A Laplacian Pyramid Based Depth Residuals model is added to the generator which reduces the difficulty of generating fog images caused by the degradation of water surface image and improves the quality of generated images. Finally, fog images are generated from sunny weather images collected with HUST-12C by LPBDR-GAN model and experiments show that generated images are very close to real fog images.

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Fast ADMM algorithm with efficient communication for distributed optimization of multi-agent systems

Fast ADMM algorithm with efficient communication for distrib...

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2021 China automation Congress, CAC 2021

作者： Cao, Shuang Jiang, Xiaowei Chi, Ming Zhang, Xianhe School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems Engineering Research Center of Intelligent Geodetection Technology Ministry of Education Wuhan China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China School of Electrical Engineering and Automation Hubei Normal University Huangshi China

ISBN: (纸本)9781665426473

This paper proposes a distributed optimization algorithm based on alternating direction method of multipliers (ADMM) for the distributed optimization problem of multi-agent systems, called ADMM with adaptive penalty terms and conditional communication (for short, AAPCC), by using the local information of agents to update the adaptive penalty terms to speed up the convergence speed while by restricting the communication conditions of agents to reduce the communication cost of agents in the iterative process. Thus, the communication cost of the system is reduced while the convergence speed is ensured. Numerical simulation experiments show that in a multi-agent system, compared with the classical ADMM, AAPCC can better balance the convergence speed and communication cost, suitable for multi-agent systems that require fast convergence speed and less communication cost. © 2021 IEEE

关键词： Multi agent systems

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Photovoltaic Data Cleaning Method Based on DBSCAN Clustering, Quartile Algorithm and Pearson Correlation Coefficient Interpolation Method

Photovoltaic Data Cleaning Method Based on DBSCAN Clustering...

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Energy, Electrical and Power Engineering (CEEPE), International Conference on

作者： Biyuan Wang Xingye Deng Taowei Chen Yidong Li Huizhou Power Supply Bureau Guangdong Power Grid Co Guangdong China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation China University of Geosciences Wuhan China

The proportion of photovoltaic power generation in the global energy structure is increasing year by year. Because of its volatility and periodicity, grid-connected photovoltaic challenges the safe and stable operation of power grid. One of the ways to solve this problem is data mining. Data mining needs high-quality data support, and data cleaning is one of the important means to improve data quality. Aiming at the problem of poor quality of original PV data, this paper analyzes two typical outliers of PV data and proposes a PV output data cleaning method based on Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm, quartile algorithm and Pearson correlation coefficient interpolation method. Comparison of DBSCAN clustering algorithm combined with the quartile method of outlier identification with the quartile method alone outlier identification, the effectiveness of the method proposed in this paper is verified. Then using the method proposed in this paper for outlier identification based on Pearson correlation coefficient interpolation and cubic spline interpolation to verify the data filling effect, the results show that Pearson correlation coefficient interpolation is superior to cubic spline interpolation. Finally, two sets of data with different data cleaning methods are substituted into the Long short-term memory (LSTM) Model to verify accuracy of the cleaning method proposed in this paper.

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Recursive Filtering for Time-Varying Nonlinear Delayed systems with Stochastic Parameter Matrices and Censored Measurements

Recursive Filtering for Time-Varying Nonlinear Delayed Syste...

引用

第42届中国控制会议

作者： Shuo Yang Jun Hu Peixia Gao Ruijie Dong Zhihui Wu Department of Applied Mathematics Harbin University of Science and Technology Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems Harbin University of Science and Technology School of Automation Harbin University of Science and Technology

This paper discusses the design problem of recursive filtering method for time-varying nonlinear delayed systems(NDSs) with stochastic parameter matrices(SPMs) and censored *** particular,the Tobit Type Ⅰ model provides a description of the censored *** main objective of this paper is to construct a recursive filter for NDSs with both SPMs and censored *** upper bound of the filtering error covariance is first calculated via mathematical induction,and the upper bound is then minimized by choosing proper filter ***,a sufficient condition is provided to guarantee that the filtering error is uniformly bounded in the mean-square ***,the viability and applicability of the proposed filterin g method are demonstrated using a numerical simulation.

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A Trajectory Tracking Method using Dynamic Sliding Mode control with Parameter Optimization for Autonomous Underwater Vehicles

A Trajectory Tracking Method using Dynamic Sliding Mode Cont...

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Industrial Cyber-Physical systems (ICPS)

作者： Weiliang Li Xuzhi Lai Sheng Du Chengda Lu Yawu Wang Zonghuan Chen Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China Guangzhou Marine Geological Survey Guangzhou China

Autonomous underwater vehicles (AUVs) must be able to track a particular trajectory when performing various tasks. Sometimes, the widely used control method in actual marine engineering, the proportional integral derivative (PID) control method cannot meet the accuracy requirements of AUVs' trajectory tracking. In this paper, a dynamic surface sliding mode controller for trajectory tracking is designed. A nonlinear disturbance observer is used to compensate for environmental interference, and an improved particle swarm optimization with dynamic inertia weight is applied to optimize the control parameter. Simulation experiments are based on the mathematical model of an underwater robot BLUEROV2, and the control and optimization algorithms are designed.

关键词： Autonomous underwater vehicles Trajectory tracking Heuristic algorithms Mathematical models Trajectory Vehicle dynamics Particle swarm optimization

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Distributed Resilient State Estimation for Time-Varying Fractional-Order Discrete complex Networks with Encoding-Decoding Scheme

Distributed Resilient State Estimation for Time-Varying Frac...

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第42届中国控制会议

作者： Yu Chen Jun Hu Jiaxing Li Aozhan Zhou Hui Yu Department of Applied Mathematics Harbin University of Science and Technology Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems Harbin University of Science and Technology School of Automation Harbin University of Science and Technology

In this paper,the distributed state estimation method with resilient attenuation feature is proposed for time-varying fractional-order complex networks under encoding-decoding *** encoding-decoding-induced dynamic errors for distinct nodes are characterized by the truncated Gaussian *** order to compensate the effects induced by encodingdecoding scheme,the variances of encoding-decoding-induced dynamic errors are considered in process of designing the resilient distributed estimation *** particular,the upper bounds of updated estimation error covariances are derived ***,the upper bounds are minimized by constructing the gain matrices at each sampling ***,a sufficient condition is provided to guarantee the boundedness of estimation error dynamics in the mean-square ***,the validity of distributed resilient state estimation scheme is demonstrated by a simulation example.

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Outlier-Resistant Distributed Filtering for Multi-Rate Nonlinear systems under Amplify-and-Forward Relays

Outlier-Resistant Distributed Filtering for Multi-Rate Nonli...

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第42届中国控制会议

作者： Shuting Fan Jun Hu Chaoqing Jia Hairui Zhao Department of Applied Mathematics Harbin University of Science and Technology Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems Harbin University of Science and Technology School of Automation Harbin University of Science and Technology

In this paper, the outlier-resistant distributed filtering problem based on amplify-and-forward relays is studied for discrete time-varying nonlinear multi-rate systems with multiple measurement delays over sensor networks, where the augmenting method is utilized to transform the multi-rate system into a single rate system. An amplify-and-forward(AF) relay is set between the sensor and the filter to extend the transmission distance of the signal and ensure the communication transmission *** outlier-resistant distributed filter is constructed by introducing a saturation function to limit the innovations, then the upper bound on the filtering error covariance is obtained and the filter gain is designed to minimize such obtained upper bound. Finally,a numerical example is used to show the effectiveness of the outlier-resistant distributed filtering algorithm based on AF relays.

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Koopman Operator Learning control of the Piezoelectric Actuator

Koopman Operator Learning Control of the Piezoelectric Actua...

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第42届中国控制会议

作者： Xiang Huang Hai-Tao Zhang School of Artificial Intelligence and Automation the Engineering Research Center of Autonomous Intelligent Unmanned Systems the Key Laboratory of Image Processing and Intelligent Control and the State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology

The piezoelectric actuator is one kind of device that can drive nanoscale motion. However, the nonlinear hysteresis effect induced by its natural material greatly degrades its positioning accuracy. To handle this challenging issue, this work develops a Koopman model predict control(Koopman-MPC) framework for the piezoelectric actuator. Specifically, the Koopman operator theory is adapted for modeling the piezoelectric actuator dynamics. A simple yet powerful linear model spanned in a high-dimensional space is thus constructed to characterize the hysteresis dynamics. Subsequently, upon the established Koopman model, an MPC scheme is put forward for tracking control of piezoelectric actuators. Therein, by sustained optimizing a cost function containing future outputs and control increments, the control input is obtained. Moreover, extensive tracking simulations are carried out on a simulated piezoelectric actuator for verifying the feasibility and effectiveness of the Koopman-MPC scheme.

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Safe Reinforcement Learning for Social Motor Coordination in Two Dimensional Space 26

Safe Reinforcement Learning for Social Motor Coordination in...

引用

26th International Conference on Industrial Technology, ICIT 2025

作者： Yang, Fan Huang, Yuening Zhai, Chao Zhang, Hehong China University of Geosciences School of Automation Wuhan Campus China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Rice University George R. Brown School of Engineering and Computing HoustonTX United States Fuzhou University School of Computer and Data Science Fuzhou China

ISBN: (纸本)9798331521950

This paper presents an interactive motion control method based on reinforcement learning, designed to assist children with autism who have social motor impairments through a mirror game intervention. The virtual teacher uses the Deep Deterministic Policy Gradient (DDPG) algorithm to optimize its actions, guiding the participant to follow a Lissajous trajectory. To ensure safety, a motion-correction mechanism was developed, which automatically adjusts actions when the predicted trajectory surpasses predefined safety boundaries. The reward function considers both the distance between the virtual teacher and the target trajectory, as well as the distance between the virtual teacher and the participant, with dynamic adjustments applied by the motion-correction mechanism. Experimental results demonstrate that the virtual teacher effectively guides the participant towards the target trajectory while adhering to safety constraints. © 2025 IEEE.

关键词： Reinforcement learning

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