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检索条件"任意字段=13th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2024"

共 716 条记录，以下是141-150 订阅

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Design and Application of Integrated Condition Monitoring and Diagnostic Architecture for Airborne systems 13

Design and Application of Integrated Condition Monitoring an...

引用

13th ieee data driven control and learning systems conference, ddcls 2024

作者： Li, Chen Huang, Jinjin Pei, Jie Air Force Engineering University Aviation Maintenance Nco School Xinyang464000 China

ISBN: (纸本)9798350361674

According to the requirements of high security, high reliability and easy maintenance of the airborne system, the comprehensive condition monitoring and diagnosis architecture based on the 'health management domain' is proposed to solve the problem of comprehensive integration of the state monitoring and diagnosis of the airborne system under multi-platform and multi-scenario conditions. this architecture proposes the comprehensive state monitoring method of general modules, functional threads and bus network according to the high integration design characteristics of the airborne system, so as to improve the online health perception capability of the onboard system without increasing hardware. It designs the health assessment and diagnosis model, proposes the multi-model integration algorithm framework of data fusion, and solves the application problem of multi-platform diagnostic model integration in the airborne system. Additionally, it also develops the graphical health management display and control interface and object-oriented health management database, and improves the interface friendliness and functional scalability of the health management system. this provides a reference for the development of the condition monitoring and diagnosis subsystem of the airborne system. © 2024 ieee.

关键词： Electronic health record

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MFALC control of Aquaculture Vessel Based on Improved ILOS Guidance Law 13

MFALC Control of Aquaculture Vessel Based on Improved ILOS G...

引用

13th ieee data driven control and learning systems conference, ddcls 2024

作者： Chen, Xianghao Yao, Wenlong Chi, Ronghu Cui, Zhigang College of Automation and Electronic Engineering Qingdao University of Science and Technology Qingdao266100 China

ISBN: (纸本)9798350361674

To mitigate the impact of lateral deviation in the trajectory control of aquaculture vessels, an improve ILOS guidance law is proposed. Addressing complex sea conditions, unstable weather scenarios, and uncertainties in load, a model-free adaptive learning control (MFALC) method for aquaculture vessel heading control is introduced. Firstly, by incorporating the actual vessel position, desired trajectory, and the improved ILOS guidance law, the desired heading is obtained, and a dynamic linearization model is established solely based on input-output data. Secondly, a Pseudo-Partial Derivative (PPD) estimation algorithm is presented. Subsequently, the MFALC control is designed in conjunction with the PPD algorithm. Finally, the superiority of the proposed control method over traditional PID control is validated through simulations. Simulation results demonstrate that the proposed control method enables rapid and stable trajectory control for aquaculture vessels. © 2024 ieee.

关键词： Aquaculture

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Real-time Trajectory Planning for Hypersonic Entry Flight via Curriculum Reinforcement learning 13

Real-time Trajectory Planning for Hypersonic Entry Flight vi...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Peng, Gaoxiang Wang, Bo Lei, Liu Fan, Huijin Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9798350361674

the paper presents a novel curriculum reinforcement learning (CRL) approach for real-time entry trajectory planning in uncertain environments and diverse tasks. the trajectory planning problem is divided into two stages: achieving a given total range goal with the satisfaction of path constraints and longitudinal state conditions and realizing real-time entry trajectory planning under comprehensive state and path constraints. the first stage employs simplified motion models, while the second stage incorporates complete 3D models. In the CRL framework, the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm is employed to train policies for both stages. the second stage policy is trained based on the first stage policy. the effectiveness and adaptability of the proposed algorithm are demonstrated through simulations, which encompass various flight missions, including emergency entry and target changes. the CRL method proves to be a valuable tool for overcoming exploration challenges in real-time entry trajectory planning. © 2024 ieee.

关键词： Reinforcement learning

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Distributed control of Multiple Electric Springs based on Droop and Consensus control in Microgrid 13

Distributed Control of Multiple Electric Springs based on Dr...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Wang, Hao Xu, Dezhi Yang, Weilin Huang, Wentao Pan, Tinglong School of Internet of Things Engineering Jiangnan University Wuxi214122 China School of Electrical Engineering Southeast University Nanjing210096 China

ISBN: (纸本)9798350361674

Aiming to address frequency fluctuation and output power imbalances in renewable energy grid connections, this paper proposes a strategy for distributed multilevel control of Electric Springs (ESs) to stabilize bus node voltage and equalize output power. Primary control utilizes the backstepping method to stabilize critical load voltages. Secondary control employs a collaborative approach of droop and consensus adaptive virtual impedance to facilitate ES control with or without communication. Under normal circumstances, consensus control enhances output power control accuracy. In the absence of communication, droop control independently obtains node voltage for backstepping reference voltage correction. Simulation verification demon-strates the proposed method's fast dynamic response, high control accuracy, and robustness. © 2024 ieee.

关键词： Microgrids

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Observer-Based Distributed Model-Free Fixed-Time Sliding Mode control for Multi-Linear Motors Speed Consistency 13

Observer-Based Distributed Model-Free Fixed-Time Sliding Mod...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Hu, Guanyang Pan, Tinglong Xu, Dezhi Yang, Weilin School of Internet of Things Engineering Jiangnan University Wuxi214122 China School of Electrical Engineering Southeast University Nanjing210096 China

ISBN: (纸本)9798350361674

For multi-linear motor systems, each motor subsystem can communicate with its neighbors through communication topology to achieve collaborative work. therefore, the multi-linear motor system can be regarded as typical multi-agent systems (MASs). this paper proposes a distributed model-free fixed-time sliding mode control (SMC) approach to tackle of the problem of multi-linear motors speed consistency. Firstly, using the ultralocal model to build the mathematical model for agents, enhanced the robustness of MAS. Moreover, to achieve the fixed-time consensus tracking, a distributed fixed-time SMC approach is proposed, which can ensure that the convergence time's upper bound remains unaffected by the initial state of MASs. Finally, some simulations based on Matlab/Simulink are provided, which indicate the feasibility and superiority of the proposed method. © 2024 ieee.

关键词： MATLAB

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Robust Adaptive Optimal control of a DC Motor System Based on Policy Iteration 13

Robust Adaptive Optimal Control of a DC Motor System Based o...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Li, Yahui Xu, Dengguo Huang, Jiashun Ma, Yan School of Automation Guangxi University of Science and Technology Liuzhou545616 China School of Physics and Electrical Engineering Liupanshui Normal University Liupanshui553004 China

ISBN: (纸本)9798350361674

In this paper, robust optimal control method is used to deal with the speed regulation of a DC motor. Considering the parameter uncertainty, a state space model of the DC motor system is established. To enable the DC motor to track a predetermined speed, the integral variable of tracking error is augmented to the state variable. the tracking problem is transformed into the robust control problem of augmented uncertain linear systems. then the robust control problem is converted into solving an optimal control with appropriate performance index. Moreover, a policy iteration algorithm in reinforcement learning is proposed to obtain a robust control law for the uncertain motor system, which enables the system output to asymptotically track an ideal signal. And the convergence of the proposed algorithm for the robust optimal control of uncertain linear systems is proved. the advantage of designing controllers through online policy iteration in reinforcement learning is without knowing the nominal system matrix. Finally, the effectiveness of the algorithm is verified by a numerical simulation example. © 2024 ieee.

关键词： Reinforcement learning

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Modified Deep Deterministic Policy Gradient Based Optimal Speed Tracking Strategy for PMSMs 13

Modified Deep Deterministic Policy Gradient Based Optimal Sp...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Fan, Zhong-Xin Tang, Lintao Li, Shihua Liu, Rongjie School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Florida State University Department of Statistics TallahasseeFL32304 United States

ISBN: (纸本)9798350361674

Achieving optimal speed regulation for permanent magnet synchronous motors (PMSMs) remains a challenging task, particularly in selecting the most suitable controller to meet desired objectives. this paper considers the optimal speed tracking problem of PMSMs. We employ a reinforcement learning algorithm to obtain optimal controller with a linear form. the reinforcement learning approach incorporates a critic-actor network structure, which approximates the value function and optimal control, respectively. Specifically, a weight updating method for the critic network is introduced, where the update of the actor network is guided by the critic network. through data collection and neural network training, dynamic acquisition of the optimal controller gain is achieved. In addition, a novel activation function is implemented in the network, leading to improved control performance concerning dataset size and reduced training time. At final, a real-world PMSM application is presented along with comparisons to demonstrate effectiveness. the desire idea of resulting optimal controllers is not only applicable to linear systems but also capable of approximating arbitrary nonlinear optimal controllers, thus offering practical engineering versatility. © 2024 ieee.

关键词： Reinforcement learning

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Interval Observer Based Fault Diagnosis for Wastewater Treatment Biological Processes 13

Interval Observer Based Fault Diagnosis for Wastewater Treat...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Zhou, Meng Wu, Yan Zhu, Zhicheng Wang, Jing Xue, Tonglai School of Electrical and Control Engineering North China University of Technology Beijing100144 China Inner Mongolia Ecological Environment Supervision Technical Support Center Hohhot010011 China

ISBN: (纸本)9798350361674

this paper proposes an interval observer based fault diagnosis method for the biological growth process in wastewater treatment. First, the nonlinear microbial growth model is transformed into a Takagi-Sugeno (T-S) fuzzy model with unknown but bounded disturbances and measurement noise. then, considering H∞ disturbance attenuation conditions, a T-S interval observer is designed for the obtained T-S fuzzy system to obtain interval boundaries of the states. Furthermore, an interval residual can be calculated by the interval states. Next, the sensor fault signals can be detected by examing that whether zero belongs to the residual interval. Finally, simulation results are presented to validate the feasibility of the proposed fault diagnosis method in wastewater treatment biological processes. © 2024 ieee.

关键词： Fuzzy systems

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Decentralized control on High-Speed Trains Based on State Observation 13

Decentralized Control on High-Speed Trains Based on State Ob...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Dong, Xudong Zhang, Jilie School of Information Science and Technology Southwest Jiaotong University Chengdu611756 China

ISBN: (纸本)9798350361674

It is well known that the dynamic model of high-speed trains are difficult to be accurately modeled, due to the air resistance shows nonlinear characteristics, and other resistances also be obtained by some empirical formulas. the above resistances are regarded as a real-time disturbance for train. Hence it has a significant adverse impact on train operation. Here, a cooperative controller based on a expansion state observation is proposed to estimate these resistances. the proposed control allows each car to be controlled asynchronously according to the railroad conditions in order to achieve high tracking performance of the speed profile and minimization of internal forces, which will greatly improve the punctuality and safety of high-speed trains. In addition, the observer is also designed based on a reduced-order system to reduce the design parameters. Train and coupler lengths are also considered to fully analyze the train dynamics associated with interaction forces as the train passes through complex road conditions. © 2024 ieee.

关键词： Decentralized control

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Microgrid Economic Dispatch Problem Based on Distributed Algorithm in V2G Background 13

Microgrid Economic Dispatch Problem Based on Distributed Alg...

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13th ieee data driven control and learning systems conference, ddcls 2024

作者： Ren, Lina Li, Shuai Hu, Zhihan Yanshan University Key Lab of Industrial Computer Control of Hebei Province Qinhuangdao066004 China

ISBN: (纸本)9798350361674

With the emergence of increasingly complex modern energy networks, there is a need for flexible and reliable methods to solve economic dispatch problems in smart grids. For this purpose, a broadcast gossip algorithm is proposed for solving the economic dispatch problem in a smart grid environment populated with distributed generators and vehicle to grid. First, with the objective of minimizing the system cost, the cost model of each part of the microgrid is developed under various constraints. At the same time, considering the peak-to-valley difference in the process of electric energy dispatching, this paper proposes an electric vehicle incentive and compensation cost model to achieve the purpose of making the grid peak and valley reduction. then, an event triggering mechanism is introduced to save communication resources while economical scheduling. Finally, the proposed model and algorithm are simulated and analyzed by using the microgrid structure of ieee 11 - bus standard, and the effectiveness of the proposed model and algorithm are verified. © 2024 ieee.

关键词： Vehicle-to-grid

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