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检索条件"任意字段=8th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2019"

共 336 条记录，以下是61-70 订阅

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Adaptive reinforcement learning tracking control for second-order multi-agent systems 8

Adaptive reinforcement learning tracking control for second-...

引用

8th ieee data driven control and learning systems conference, ddcls 2019

作者： Bai, Weiwei Cao, Liang Dong, Guowei Li, Hongyi School of Automation Guangdong Province Key Laboratory of Intelligent Decision and Cooperative Control Guangdong University of Technology Guangzhou510006 China

ISBN: (纸本)9781728114545

In this paper, the adaptive reinforcement learning tracking control problem is studied for second-order pure-feedback multi-agent systems (MASs). the pure-feedback MASs are transformed into strict-feedback form by using the mean value theorem. the reinforcement learning approach is applied to handle the unknown functions and system control performance index. Moreover, the error terms are introduced to the controller, which can improve the robust of the control scheme. the theoretical analysis indicates that all the signals and tracking errors in close-loop system are semi-global uniformly ultimately bounded (SGUUB), and the numerical simulation are conducted to verify the superiority of this scheme. © 2019 ieee.

关键词： Reinforcement learning

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data-driven online adaptive optimal control for linear systems with completely unknown dynamics 8

Data-driven online adaptive optimal control for linear syste...

引用

8th ieee data driven control and learning systems conference, ddcls 2019

作者： Zhao, Jun Na, Jing Gao, Guanbin Xiao, Yuyao Song, Zhuoyue Kunming University of Science and Technology Faculty of Mechanical and Electrical Engineering Kunming650500 China School of Optics and Photonics Beijing Institute of Technology Beijing10081 China School of Automation Beijing Institute of Technology Beijing10081 China

ISBN: (纸本)9781728114545

this paper develops a novel method to address the optimal control problem of systems with unknown dynamics. An adaptive identifier is first constructed based the the vectorization operator and Kronecker products, where we can reconstruct the unknown system dynamics based on the measurable input and output data. A recently proposed adaptive law is used to guarantee the convergence of the identifier parameters. then, a data-driven technology is applied to online solve the derived algebraic Riccati equation (ARE). For this purpose, we apply the Kronecker's products on the ARE such that another adaptive law is employed to online estimate the parameters involved in the ARE with guaranteed convergence. Simulation results are given to illustrate the effectiveness of the proposed method. © 2019 ieee.

关键词： Linear systems

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IRL method for time-continuous two-player nonzero sum game of unknown system with constrained-input 8

IRL method for time-continuous two-player nonzero sum game o...

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8th ieee data driven control and learning systems conference, ddcls 2019

作者： Ren, He Zhang, Huaguang Wen, Yinlei Mu, Yunfei State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110004 China

ISBN: (纸本)9781728114545

this paper addresses an off-policy method for solving the optimal control problem of the two-player nonzero sum (NZS) game when the inputs are constrained. Benefit from integral reinforcement learning (IRL) technology, proposed method can achieve the optimal solutions when the system dynamics can hardly obtained in practical applications. the equivalent convergency proof of the proposed method is also figured out. Actor-critic framework is constructed by utilizing the neural networks (NNs), in detailed the actor NNs are employed to approach the optimal control meanwhile the critic NNs are employed to approach the value functions. At last, a simulation is supplied to show the accuracy and effectiveness of the method we proposed. © 2019 ieee.

关键词： Reinforcement learning

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Shipwrecks detection based on deep generation network and transfer learning with small amount of sonar images 8

Shipwrecks detection based on deep generation network and tr...

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8th ieee data driven control and learning systems conference, ddcls 2019

作者： Xu, Lixue Wang, Xiubo Wang, Xudong Harbin Engineering University Department of Automation Harbin150001 China Heilongjiang Institute of Geological Surveying and Mapping Harbin150000 China

ISBN: (纸本)9781728114545

the application of deep learning sonar target detection is severely limited due to the small amount of sonar images, especially for submarine shipwreck. Aiming to overcome the over-fit of training problem and improve accuracy of detection, we proposed a method which combine deep generation networks and transfer learning for sonar shipwrecks detection. Specifically, in deep generation network, we used similarity measurement to improved optimization, which generate high quality fake image and laid the further foundation of data. then, in transfer learning detection, we used multi-layer adaptation and multi-core MMD to fine-tune and frozen pre-trained model, prevent the problem of over-fit and improve the generalization and stability of the system. And we combined the methods of regional suggestion and regression for target detection to guarantee precision of detection. Finally, the contrast experiment of sonar shipwrecks is carried out the effectiveness of the proposed method. © 2019 ieee.

关键词： Image enhancement

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A new quality control method for cotton spinning 8

A new quality control method for cotton spinning

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8th ieee data driven control and learning systems conference, ddcls 2019

作者： Shao, Jingfeng Yang, Xiaoyu Ma, Chuangtao School of Management Xi'An Polytechnic University Xi'an710048 China

ISBN: (纸本)9781728114545

To identify the irregular fluctuation of the spinning quality, and to control abnormal behavior of influencing factors in the spinning process, first, through massive spinning data, fluctuation reasons of the spinning quality output characteristic values were analyzed from influencing factors (human, equipment, environment, and etc.), and then computed the correlation degree among influencing factors and quality characteristics values. Second, through the theory of probability statistics, a linear relationship between influencing factors and quality characteristic values was built, and then generation mechanism, interaction relationship and behavioral characteristics of influencing factors were explored. Finally, an intelligent control method for the spinning quality was proposed. As verified by application practice, the proposed method has achieved a full range control of the fluctuation regular of the spinning quality, which are from fluctuation reason to generation mechanism, and to mutual relationship and behavior identification of influencing factors. © 2019 ieee.

关键词： Intelligent control

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A modified data-driven regression model for power flow analysis 8

A modified data-driven regression model for power flow analy...

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8th ieee data driven control and learning systems conference, ddcls 2019

作者： Qin, Chun Wang, Linqing Han, Zhongyang Zhao, Jun Wang, Wei School of Control Science and Engineering Dalian University of Technology Dalian116023 China

ISBN: (纸本)9781728114545

As one of the most important procedure in system recognition, Power Flow (PF) analysis is the pivotal basis of achieving optimal operation and production. Due to the difficulty of obtaining system parameters, low calculation accuracy and high computation costs, model-driven approaches, such as DC Power Flow (DCPF), cannot provide satisfied results for real application. While with the massive accumulated data from industrial enterprise, data-driven linearization approaches of PF become an effective alternative. In this paper, we propose a modified data-driven regression model that reveals the mapping rules between the known and unknown variables in power system. then, the update mode of this model is further derived, which facilitates PF calculations with different variations of bus types. A regression model of network loss is also built so as to reflect the efficiency of the system as well as enhance comprehensiveness of the proposed data-driven PF analysis. the experimental results of 8 standard test systems demonstrate that the proposed model has a significant improvement on both computational accuracy and computation speed comparing with model-driven approaches and the inverse regression model of PF. © 2019 ieee.

关键词： Electric load flow

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Multiple fault diagnosis for sucker rod pumping systems based on matter element analysis with f-statistics 8

Multiple fault diagnosis for sucker rod pumping systems base...

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8th ieee data driven control and learning systems conference, ddcls 2019

作者： Han, Ying Li, Kun Ge, Fawei College of Engineering Bohai University Jinzhou121013 China

ISBN: (纸本)9781728114545

Dynamometer cards can reflect different down-hole working conditions of sucker rod pumping wells. It has great significances to realize multiple fault diagnosis for actual oilfield production. In this paper, the extension theory is used to build a matter-element model to describe the fault diagnosis problem of the sucker rod pumping wells. the correlation function is used to calculate the correlation degree between the diagnostic fault and many standard fault types. the diagnosed sample and many possible fault types are divided into different combinations according to the correlation degree;the F-statistics of each combination is calculated and the 'unbiased transformation' is used to find the mean of interval vectors. Larger F-statistics means greater differences within the faults classification;and the minimum F-statistics reflects the real multiple fault types. Case study shows the effectiveness of the proposed method. © 2019 ieee.

关键词： Failure analysis

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Trajectory tracking control of hydraulic rehabilitation exoskeleton leg with output constraint 8

Trajectory tracking control of hydraulic rehabilitation exos...

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8th ieee data driven control and learning systems conference, ddcls 2019

作者： Yang, Yong Dong, Xiucheng Wang, Xiaoping Huang, Deqing School of Electrical Engineering and Electronic Information Xihua University Chengdu610039 China Institute of Systems Science and Technology Southwest Jiaotong University Chengdu610031 China

ISBN: (纸本)9781728114545

this paper addresses the trajectory tracking control of lower limb rehabilitation exoskeleton leg driven by hydraulic actuator with output constraint. A barrier Lyapunov function is utilized to handle the output constraint of the hydraulic actuator. the radial basis functions neural networks are used to approximate the disturbance and unmodeled uncertainties. Under the effect of the designed control scheme, the output constraint problem is well averted, and the involved signals of the rehabilitation exoskeleton are semi globally bounded. the tracking convergence of the closed-loop system is demonstrated by using mathematical method. the performance of the designed controller is illustrated by numerical simulations. © 2019 ieee.

关键词： Lyapunov functions

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Energy consumption optimization for public buildings by using data-driven heuristic dynamic programming algorithm 8

Energy consumption optimization for public buildings by usin...

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8th ieee data driven control and learning systems conference, ddcls 2019

作者： Shi, Mingrui Yang, Xu Liu, Xudong Cui, Jiarui Huang, Jian Tong, Chaonan Key Laboratory of Knowledge Automation for Industrial Processes School of Automation and Electrical Engineering University of Science and Technology Beijing Ministry of Education Beijing100083 China

ISBN: (纸本)9781728114545

this paper proposes an optimization method on energy consumption for public buildings based on the data-driven heuristic dynamic programming algorithm. To this end, a large amount of building data is first collected from a well-established monitoring system, including electricity, environmental information and human behaviors. According to this, the model network of HDP structure is then proposed by using BP neural network, furthermore, the optimal weights of action network and critic network are solved during the iteration process of HDP. At last, the performance and the effectiveness of HDP optimization are demonstrated through a case study of a building energy consumption monitoring system from practical engineering viewpoint. © 2019 ieee.

关键词： Buildings

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Model analysis and design of 3d printing control system based on cement components 8

Model analysis and design of 3d printing control system base...

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8th ieee data driven control and learning systems conference, ddcls 2019

作者： Lu, Hongqian Wang, Renren School of Electrical Engineering and Automation Qilu University of Technology Shandong Academy of Sciences Shandong China

ISBN: (纸本)9781728114545

this design mainly analyzes and designs a 3D printing equipment model based on extrusion curing of raw materials. the working principle of the device is that the CAD model of the building to be printed is first used, and the program is written directly by point-by-point comparison interpolation method. the program is then stored as a device control system. When printing is required, only the corresponding program is called. And the system will control the servo driver, drive the servo motor, the servo motor drives the mechanical arm sprinkler head to move on the XYZ axis through the gear drive. At the same time, the system sends out a signal to drive the feeding motor to drive the screw rod to start feeding. the electromagnetic valve of the nozzle opens and starts to print and construct the building according to the program written by interpolation algorithm. © 2019 ieee.

关键词： Interpolation

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