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检索条件"任意字段=9th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2020"

共 506 条记录，以下是391-400 订阅

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An adaptive unscented Kalman filter for a nonlinear fractional-order system with unknown order

An adaptive unscented Kalman filter for a nonlinear fraction...

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data driven control and learning systems (ddcls)

作者： Yue Miao Zhe Gao Xiaojiao Chen Shool of Mathematics Liaoning University Shenyang People’s Republic of China College of Light Industry Liaoning University Shenyang People’s Republic of China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

In this paper, an unscented Kalman filter (UKF) for a nonlinear fractional-order system (FOS) with the unknown order is proposed. the continuous-time nonlinear FOS is discretized by Grünwald-Letnikov difference, and the corresponding difference equation is obtained. Besides, the augmented vector is presented to establish the augmented equation with respect to the state and fractional-order, and the nonlinear functions in the nonlinear augmented equation are performed by the unscented transform. the state and unknown order are estimated by the proposed adaptive UKF to improve the accuracy of state and order estimations compare with the extended Kalman filter. Finally, two examples are given to verify the effectiveness.

关键词： Kalman filters Estimation Mathematical model Difference equations Calculus Noise measurement Adaptive systems

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Adaptive Dynamic Programming Method for Optimal Battery Management of Battery Electric Vehicle

Adaptive Dynamic Programming Method for Optimal Battery Mana...

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data driven control and learning systems (ddcls)

作者： Jiguang Xue Chunsheng Yan Dan Wang Jun Wang Jun Wu Zehua Liao Electric Power Research Institute of State Grid Liaoning Electric Power Co. Ltd Shenyang China LiaoNing Electric Power Development Stock Co. LTD Shenyang China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

One of the main influencing factors of battery electric vehicle (BEV) application is the high-cost of the battery. We consider to apply the battery of BEV to smart residential environments when the BEV is idle, so that we can lower the utility cost. therefore, an adaptive dynamic programming (ADP) method is designed to solve the optimal battery management, which avoids the dimension disaster of the complex nonlinear BEV system. First, the operation modes of the battery are analyzed, and the problem statement is carried out. then, the corresponding self-learning optimization algorithm is developed based on ADP. Finally, numerical results by experiment simulations are used to verify the ADP algorithm.

关键词： Batteries Optimal control Dynamic programming Battery management systems Power grids Discharges (electric) Adaptation models

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Multi-label Disease Diagnosis Based on Unbalanced ECG data

Multi-label Disease Diagnosis Based on Unbalanced ECG Data

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data driven control and learning systems (ddcls)

作者： Peishan Rong Tao Luo Jianfeng Li Kai Li Beijing University of Posts and Telecommunications Beijing China First Research Institute of the Ministry of Public Security Beijing China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

With the improvement of living standards, heart diseases have become one of the common diseases that threaten health of human beings. Electrocardiogram (ECG) is an important basis for diagnosing heart diseases. In this paper, we propose a model to predict 55 classes of heart diseases simultaneously, that is, to solve a multi-label classification task. In order to make full use of the characteristics of the ECG, we propose a network structure combining residual neural network (ResNet) and gated recurrent unit neural network (GRU). On this basis, in order to solve the problem of imbalanced data set, the loss function is a improved focal loss. the results of experiments show the effectiveness of our method. More specifically, the method improves F1 score, while the hamming loss is reduced. Observing the classify result of each single class, we improve F1 score and average area under the receiver operating characteristic curve (AUC) for most classes.

关键词： Heart learning systems Neural networks Electrocardiography Predictive models Feature extraction Diseases

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Load frequency control of three-area interconnected power systems based on reduced-order active disturbance rejection controller

Load frequency control of three-area interconnected power sy...

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data driven control and learning systems (ddcls)

作者： Yuemin Zheng Zengqiang Chen Zhaoyang Huang Mingwei Sun Qinglin Sun College of Artificial Intelligence Nankai University Tianjin China Key Laboratory of Intelligent Robotics of Tianjin Tianjin China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

A reduced-order Linear Active Disturbance Rejection control (LADRC) controller for the load frequency control (LFC) system is studied in this paper. the power system is inevitably disturbed by various factors such as temperature and pressure, which may cause instability of the frequency and bring safety problems. the ADRC controller has the characteristic of estimating the disturbance and then eliminating it to achieve the suppression of disturbance. therefore, the ADRC controller, theoretically speaking, can be used to solve the LFC problems. We utilize the reduced-order LADRC controller to control a three-area interconnected power system, and the simulation results show that the performance of the reduced-order ADRC controller is better than that of the traditional PID controller. Finally, we verified the robustness of the designed controller by changing the parameters of the controlled object.

关键词： Frequency control Time-frequency analysis control systems Power system stability Observers Mathematical model Frequency estimation

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Unconditional Secure Topology-hiding Broadcast Via Shamir’s Secret Sharing

Unconditional Secure Topology-hiding Broadcast Via Shamir’s...

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data driven control and learning systems (ddcls)

作者： Bo Mi Bingqing Wu Fengtian Kuang Huang darong Shijie Wu Mengting Lin Academy of Information Science and Engineering Chongqing Jiaotong University Chongqing China Unit 78156 of the Chinese people’s Liberation Army

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

Secure Multi-Party Computation is a hot topic in recent years. However, though Secure Multi-Party Computation allows each participant to calculate without making their information known to other nodes, the underlying topology of their network is prone to exposure. Inspired by Tal Moran, Bo Mi et al. designed a broadcast protocol based on NTRUEcrypt, which realized topology-hiding but relying on a third party. In view of this shortcoming, we proposed a topology-hiding broadcast protocol based on Shamir's Secret Sharing scheme with self-adaptive paradigm. Security and performance analyses demonstrated that our scheme is unconditional secure and computationally light-weighted.

关键词： Cryptography Protocols data communication Servers Receivers Topology Interpolation

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Consensus tracking for discrete distributed parameter multi-agent systems via iterative learning control

Consensus tracking for discrete distributed parameter multi-...

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data driven control and learning systems (ddcls)

作者： Cun Wang Xisheng Dai Qingnan Huang Jingjing Wang Su Wang School of Electrical and Information Engineering Guangxi University of Science and Technology Liuzhou P. R. China School of Vocational and Technical Education Guangxi Science and Technology Normal University Laibin P. R. China Key Laboratory of Industrial Process Intelligent Control Technology of Guangxi Higher Education Institutes Liuzhou P. R. China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

In this paper, the consensus tracking problem of discrete distributed parameter multi-agent systems are studied. the communication topology of the system remains unchanged, and only some agents can directly obtain the trajectory information of the virtual leader. An iterative learning control law including the consensus error between any two agents in the system is designed, and the convergence condition of the algorithm is obtained with the help of the contraction mapping principle. In the sense of L 2 norm, the consensus tracking error among all agents in the system can converge to zero along the iteration axis. Finally, simulation examples prove the applicability of the algorithm.

关键词： Iterative learning control Convergence Multi-agent systems Trajectory Target tracking Topology Task analysis

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Iterative learning control (ILC) Guided Reinforcement learning control (RLC) Scheme for Batch Processes

Iterative Learning Control (ILC) Guided Reinforcement Learni...

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data driven control and learning systems (ddcls)

作者： Xinghai Xu Huimin Xie Jia Shi School of Chemistry & Chemical Engineering Xiamen University Xiamen P. R. China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

Iterative learning control (ILC) is a kind of effective learning control scheme which is mainly designed to solve the problems in controlling a batch or repetitive process. Although the control performances of ILC systems can improved from batch to batch, it still strongly depends on the repeatability of the process and control target. Reinforcement learning (RL) is another learning based optimization algorithm which can be applied to many complicated decision-making scenarios. data-driven based RL algorithms have good robustness due to the generalization of the policy neural network, however, it is low-data efficiency in network training. In this paper, for batch process control we propose a new reinforcement learning control (RLC) scheme which is guided by classical iterative leaning control. On the one hand, this RLC scheme has capability to optimize the policy network faster than RL algorithm without guidance, on the other hand, the generalization of deep policy network improves the robustness of the control system. Based on the numerical simulations, the effectiveness of the proposed control scheme is demonstrated by comparing with the conventional reinforcement learning algorithm and the P-type iterative learning control scheme. this paper provides a new way for the application of reinforcement learning algorithm to batch process control.

关键词： Process control Reinforcement learning control systems Batch production systems Iterative learning control Heuristic algorithms Robustness

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Disturbance Estimation and Attenuation for Repetitive-control systems with Unknown Nonlinearity

Disturbance Estimation and Attenuation for Repetitive-Contro...

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data driven control and learning systems (ddcls)

作者： Fuxi Jiang Lan Zhou Zhu Zhang Zhuang Jiang Changchao Liao School of Information and Electrical Engineering Hunan University of Science and Technology Xiangtan P. R. China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

this paper presents a framework for a class of single-input-single-output (SISO) nonlinear systems with periodic tasks and subject to aperiodic disturbances using linear-extended-state-observer (LESO)-based repetitive control method. A two-stage design procedure is devised to enhance the disturbance estimation and attenuation ability of repetitive-control system where design of LESO is separated from design of repetitive control law. An LESO is designed to estimate and compensate the nonvanishing lumped disturbance in real time fashion. the stability criterion of the LESO-based repetitive-control system is established in the presence of unknown nonlinear dynamics. the simulations demonstrate that the proposed LESO-based repetitive-control system can achieve satisfactory disturbance rejection and tracking control performances simultaneously. Furthermore, a slight correction to the amount of the delay of the repetitive controller leads to a substantial decrease in steady-state tracking error.

关键词： Observers Delays Attenuation Steady-state Nonlinear dynamical systems Estimation error Tuning

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Locality-Constrained Dictionary learning Classification Method of WCE Images

Locality-Constrained Dictionary Learning Classification Meth...

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data driven control and learning systems (ddcls)

作者： Zixin Shen Yue Ma Jinhui Zhu Sheng Li Liping Chang Qianru Jiang Xiongxiong He College of Information Engineering Zhejiang University of Technology Hangzhou P. R. China The Second Affiliated Hospital of Zhejiang University School of Medicine Hangzhou P. R. China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

Wireless capsule endoscopy (WCE) is widely used in medical diagnosis which generates lots of images for each operation. For clinicians, analyzing these images is a time-consuming and laborious task. therefore, an automatic image classification algorithm is proposed to help doctors quickly check the condition of specific organs such as stomach or small intestine in the digestive tract. In the preprocessing stage, we obtain the regions of interest from the images of cecum, pylorus and cardia followed by extracting the fused color and texture features. At the next stage, an effective organ classification method based on dictionary learning was proposed, the locality-constrained term was constructed using the profile matrix and locality information of atoms. the simulation results demonstrate that the LCDL algorithm exceeds some existing algorithms on the organ classification task.

关键词： Dictionaries Training Feature extraction Machine learning Image color analysis Image coding Image reconstruction

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A Variable Parameter Model-Free Adaptive control Algorithm and Its Application in Distillation Tower System

A Variable Parameter Model-Free Adaptive Control Algorithm a...

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data driven control and learning systems (ddcls)

作者： Yu Feng Na Dong Yongzhou Li Wenjin Lv School of Electrical and Information Engineering Tianjin University Tianjin China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

In order to achieve better control performance of chemical process, model free adaptive control (MFAC) scheme is improved by adding two new parameters L 1 , L 2 , furthermore to apply in distillation tower system. Compared with basic MFAC, the number of parameters in this novel method is reduced and variable. Firstly, nonlinear system with time-varying desired output is used to carry out numerical simulation for the sake of verifying the effectiveness of this algorithm. After that, the improved MFAC algorithm is applied to the control of the distillation tower system, and the result fully demonstrates the proposed algorithm has strong stability, fast tracking speed. At last, for many systems with time delay in chemical process, such as distillation tower system, a set of validated control method frameworks is proposed in this paper. It is expected to be universally popularized and applied to the control of chemical process.

关键词： Poles and towers Standards Mathematical model Temperature control Stability analysis Nonlinear systems Simulation

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