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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361-370 订阅

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Finite-time Annular Domain Stabilization for Nonlinear systems in Strict-feedback Form

Finite-time Annular Domain Stabilization for Nonlinear Syste...

引用

data driven control and learning systems (ddcls)

作者： Zhiguo Yan Dongkang Ji Guolin Hu Mingjun Du Xiaoping Liu School of Electrical Engineering and Automation Qilu University of Technology(Shandong Academy of Sciences) Jinan P. R. China School of Control Science and Engineering Shandong University Jinan P. R. China Lakehead University Thunder Bay ON Canada

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

the problem of finite-time annular domain stabilization for nonlinear systems in strict-feedback form is considered in this paper. Firstly, a definition of finite-time annular domain stability for nonlinear systems is given and also some practical explanation is presented. Secondly, a back-stepping design approach is proposed and a sufficient condition for the existence of finite-time annular domain stabilization controller is given. Finally, a detailed example is used to show back-stepping design approach superiority to linear matrix inequality approach.

关键词： Nonlinear systems Trajectory Asymptotic stability Stability analysis Closed loop systems Upper bound Transient analysis

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A Novel Group Consensus Protocol with Hybrid Delay for Linear Multi-agent systems

A Novel Group Consensus Protocol with Hybrid Delay for Linea...

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data driven control and learning systems (ddcls)

作者： Weixun Li Liqiong Zhang Limin Zhang College of Science Tianjin University of Technology and Education China Zhongyuan University of Technology Zhengzhou China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

In allusion to the issues of achieving group consensus of ecumenical multi-agent systems, a neoteric and comprehensive control protocol was designed neighbor-based messages of agents and distributed management of the neighborhood, which includes the three situations of the general communication delay, lagged communication delay and no communication delay. then, on account of the designed control protocol and the related knowledge of the algebra and diagram theory, group consistency matter of multi-agent systems are transformed into stability matters of deviation systems. Via using the knowledge of Lyapunov stability theory, we obtain a sufficient and indispensable criterion to ensure that multi-agent system can implement group consistence. Afterwards, theory consequences were numerically simulated in the aided by mathematical software, and the consequences show that the presented manipulative protocol capable multi-agent systems to implement multi-group consensus under certain conditions.

关键词： Protocols Multi-agent systems Delays Trajectory Topology Knowledge engineering Finite element analysis

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Synchronization control of Position and Velocity for Heterogeneous Teleoperation System

Synchronization Control of Position and Velocity for Heterog...

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data driven control and learning systems (ddcls)

作者： Xia Liu Chengwei Pan Yong Chen School of Electrical Engineering and Electronic Information Xihua University Chengdu China School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

Due to different mechanical structures, communication methods and task spaces, the master robot and the slave robot in a heterogeneous teleoperation system are difficult to keep synchronization. this paper presents a synchronization control strategy of position and velocity for the heterogeneous teleoperation system. the interaction force between the operator and the master is utilized to make the master generate the position information and position variation. the position information of the master is used to control the position of the slave. Meanwhile, the position variation of the master is employed to indirectly control the velocity of the slave. In this way, the position and velocity of the slave can be in synchronization with those of the master. the experimental results demonstrate that with the proposed control strategy the slave can act on the target more accurately and quickly, enhancing the operator's operational flexibility.

关键词： Robots Synchronization Task analysis Robot kinematics Force Aerospace electronics Service robots

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Design and Application of Intelligent Diagnosis Model Based on data driven

Design and Application of Intelligent Diagnosis Model Based ...

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data driven control and learning systems (ddcls)

作者： Guihua Zhang Jie Yao Peng Wu Chongqing Chuanyi Software Co. Ltd Chongqing China College of Automation Chongqing University Chongqing China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

In this paper, an intelligent diagnosis model is designed based on stress wave technology. the model includes two parts: primary diagnosis and advanced diagnosis. the primary diagnosis model mainly uses the K-Means algorithm to realize the function of automatic hierarchical warning. After the hierarchical warning is triggered, the advanced diagnostic model obtains multiple sets of spectrum data through systematic sampling, and uses the enumeration algorithm to select the most representative one from it to achieve automatic output of fault information and alarm functions. the intelligent diagnosis model is applied to the axial flow fan. the output of the model is the same as the analysis result of the professional, indicating that the model is well applied to the axial flow extension.

关键词： Stress Linear programming Systematics Strain Production Mathematical model Statistics

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Automatic Generation control of Isolated Two-area Microgrid with Multiple Resources Based on learning Optimization

Automatic Generation Control of Isolated Two-area Microgrid ...

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data driven control and learning systems (ddcls)

作者： Changyou Feng Penghu Wang Haiwei Wu Li Huang Hao Tang National Electric Power Dispatching and Control Center Beijing China School of Electrical Engineering and Automation Hefei University of Technology Hefei China State Grid Jiangsu Electric Power CO. LTD. Nanjing China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

this paper studies the automatic generation control (AGC) problem of isolated two-area multiple source microgrid energies under the influence of stochasticity and volatility of renewable energies and loads. A Load Frequency control (LFC) model of isolated two-area microgrid with multiple distributed energy resources and energy storage device is established. the wind power, the photovoltaic output and load fluctuation are formulated as discrete-time Markov processes based on their stochastic dynamic characteristics. the performance of the proposed learning optimization algorithm combined with the AGC principle of the power grid is demonstrated on microgrid system. At last, comparing SAQ-learning with traditional Q-learning and PI controller, simulation results illustrated the rationality of the proposed microgrid model and the expected performance of the controller.

关键词： Frequency control Microgrids Photovoltaic systems Automatic generation control Regulation Markov processes Flywheels

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A Deep Reinforcement learning Approach to the Flexible Flowshop Scheduling Problem with Makespan Minimization

A Deep Reinforcement Learning Approach to the Flexible Flows...

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data driven control and learning systems (ddcls)

作者： Jialin Zhu Huangang Wang Tao Zhang Tsinghua University Beijing P. R. China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

Recent work has demonstrated the efficiency of deep reinforcement learning (DRL) in making optimization decisions in complex systems. Compared with other DRL algorithms, the proximal policy optimization (PPO) has higher stability and lower complexity. the typical flexible flowshop scheduling problem (FFSP) with identical parallel machines is an NP-hard problem. this paper is the first case to utilize PPO to solve the problem with makespan minimization. the particular state, action and reward function are designed for the FFSP to follow the Markov property. the efficiency of PPO is evaluated on the wafer pickling instance and random instances with different scales. the results show that PPO can always provide satisfactory solutions within a reasonable computational time.

关键词： Heuristic algorithms Pickling Job shop scheduling Reinforcement learning Optimization Processor scheduling Parallel machines

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Spatial Adaptive Iterative learning control for Automatic Driving of High Speed Train

Spatial Adaptive Iterative Learning Control for Automatic Dr...

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data driven control and learning systems (ddcls)

作者： Zhenxuan Li Zhongsheng Hou Chenkun Yin Beijing Institute of Petrochemical Technology Beijing P. R. China School of Automation Qingdao University Qingdao P. R. China Beijing Jiaotong University Beijing P. R. China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

this paper develops spatial adaptive iterative learning control (SAILC) method for the Automatic Train Operation (ATO) of high speed train in order to drive the train speed to follow the desired displacement-speed trajectory. By utilizing spatial state differentiator, the temporal nonlinear train control system is transformed to a spatial nonlinear train control system. the system uncertainties which are space dependent are learned by a spatial parametric updating law. By adopting the spatial composite energy function, the convergence of the SAILC for train control system is obtained. Furthermore, the convergence of the speed error in spatial domain under iteration-varying initial speed of the proposed SAILC is made. Numerical results of the train operation are given to verify the effectiveness of the proposed SAILC method.

关键词： Resistance control systems Convergence Iterative learning control Force Adaptation models Uncertainty

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Fusion-based multi-kernel learning filter with maximum correntropy criterion

Fusion-based multi-kernel learning filter with maximum corre...

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data driven control and learning systems (ddcls)

作者： Lin Chu Wenling Li School of Automation Science and Electrical Engineering Beihang University (BUAA) Beijing P. R. China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

Kernel learning filters have been effective tools for addressing nonlinear function fitting problem. In these filters with Gaussian kernels, the performance depends on the choice of the kernel width and an inappropriate kernel width might degrade the learning performance. To further improve the learning performance, a fusion-based multi-kernel learning filter with maximum correntropy criterion is proposed in this paper, in which multiple learning filters with different kernel widths run independently and the output estimates are fused by a set of weighting coefficients. the weighting coefficients are treated as the posterior probabilities of the kernel widths in effective and they are computed recursively by using the likelihood functions. Simulation results show that the proposed filter outperforms the existing single kernel learning filters and the multi-kernel learning filter with maximum mixture correntropy criterion.

关键词： Kernel Cost function Simulation Random variables Mean square error methods Adaptive learning Weight measurement

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Intrusion Detection based on Non-negative Positive-unlabeled learning

Intrusion Detection based on Non-negative Positive-unlabeled...

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data driven control and learning systems (ddcls)

作者： Sicai Lv Yang Liu Zhiyao Liu Wang Chao Chenrui Wu Bailing Wang School of Computer Science and Technology Harbin Institute of Technology at Weihai Weihai Research Institute of Cyberspace Security Harbin Institute of Technology at Weihai Weihai China Industrial Control Systems Cyber Emergency Response Team Beijing China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

Due to the diversity of network traffic flow, intrusion detection is usually studied as an anomaly detection problem. In this paper, Positive-unlabeled with Non-negative Risk Estimator(nnPU) learning is introduced for intrusion detection. the cyber attacks is treated as positive samples in PU learning. A risk estimator is raised to estimates the binary classification loss. For data imbalance in intrusion detection, we improve the risk estimator of nnPU through focal loss(FL-nnPU). the dynamic weights in focal loss is used to balance the small class prior. the experiments result show that FL-nnPU have a close performance to binary classification, and it performs better than nnPU under data imbalance problems.

关键词： Intrusion detection data models Training Security Machine learning algorithms Support vector machines Heuristic algorithms

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data-driven Adaptive Filtering for Fault Diagnosis of A Class of Nonlinear Discrete-time systems

Data-driven Adaptive Filtering for Fault Diagnosis of A Clas...

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data driven control and learning systems (ddcls)

作者： Hongjiang Ji Lingling Fan Xindong Gui Chenkun Yin Rongmin Cao China Shipbuilding IT CO. LTD. Beijing China School of Automation Beijing Information Science & Technology University Beijing China School of Electronics and Information Engineering Beijing Jiaotong University Beijing China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

data-driven adaptive filtering technique has been widely concerned due to its extensively used in industry control system. In order to handle actuator fault diagnosis problem with a class of nonlinear discrete-time systems, this paper investigates a novel data driven adaptive filtering based on dynamic linearization technique in the framework of Kalman Filter and Recursive Least Square(RLS) algorithm. Compared with the conventional fault diagnosis algorithm, by modeling actuator faults changes, the proposed data-driven adaptive filtering for fault diagnosis (DDAF-FD) method is performed through joint state-parameter estimation and designed by only using measurement I/O data without precise mathematical model or linearization approximation. Numerical examples are presented to verify the effectiveness of the proposed algorithm.

关键词： Fault diagnosis Filtering Mathematical model Nonlinear dynamical systems Heuristic algorithms data models Adaptation models

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