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检索条件"任意字段=2021 4th International Conference on Advanced Algorithms and Control Engineering, ICAACE 2021"

共 251 条记录，以下是81-90 订阅

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Comparison of Different Strategies to Minimize Torque Ripples for Switched Reluctance Motor 4

Comparison of Different Strategies to Minimize Torque Ripple...

引用

4th IEEE China international Electrical and Energy conference, CIEEC 2021

作者： Ren, Ping Zhu, Jingwei Guo, Zhaoyan Song, Xin Jing, Zhe Xu, Aide Dalian Maritime University School of Marine Electrical Engineering Dalian China Dalian Maritime University School of Information Science and Technology Dalian China

ISBN: (纸本)9781728171494

In this paper, two novel strategies are proposed to minimize the torque ripple of switched reluctance motor (SRM), the first approach combines torque sharing function (TSF) with direct instantaneous torque control (DITC), and the second technique is the integration of model predictive control (MPC) and TSF. Firstly, the basic principles of two methods are introduced in detail and their control block diagrams are illustrated for comparison. Secondly, the proposed two control schemes are verified by the simulation in Matlab/Simulink. Finally, the simulation results show that the correctness of two schemes in terms of decrease the torque ripple. In addition, the steady and dynamic state performances of the two algorithms are compared in this paper. the study demonstrates that the MPC+TSF scheme can provide lower torque ripple and better control performance. © 2021 IEEE.

关键词： Model predictive control

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Design of control System for Concrete Mixing Plant 4

Design of Control System for Concrete Mixing Plant

引用

4th international conference on Electron Device and Mechanical engineering, ICEDME 2021

作者： Wu, Changzhong Shang, Guangchao Wu, Liang Zhao, Mingpeng University of Jinan School of Mechanical Engineering Jinan China

ISBN: (纸本)9780738114002

With the rapid development of China's infrastructure construction and the start of a series of national key projects, the demand for concrete is increasing day by day. China has become the country with the largest production and use of concrete. As the main equipment for preparing concrete and the direct supply source of concrete, concrete mixing station has become an indispensable equipment in the construction industry. Concrete is one of the most widely used building materials in civil engineering. the control system of concrete mixing station plays an important role in the technical and economic indicators of concrete production. One of the core parts of concrete mixing station is the control system. therefore, the advanced control system of concrete mixing station is of great significance for concrete production. this paper mainly focuses on the design and research of the control system of the concrete mixing station, mainly designs a control system which can detect and control the workflow of the concrete mixing station, which is helpful to analyze and solve the problems existing in the development process of the concrete mixing station. © 2021 IEEE.

关键词： control systems

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Development of MPC-ACO based Direct Torque controller for Induction Motor Drive 4

Development of MPC-ACO based Direct Torque Controller for In...

引用

4th Biennial international conference on Nascent Technologies in engineering, ICNET 2021

作者： Mohanty, Kanungo Barada Sahu, Abhimanyu Mishra, Rabi Narayan National Institute of Technology Department of Electrical Engineering Rourkela India Silicon Institute of Technology Department of Eee Bhubaneswar India

ISBN: (纸本)9781728190617

the purpose of this paper is to control the torque of a three-phase induction motor using model predictive control (MPC) with an ant colony optimization (ACO) based direct torque control (DTC) scheme in a 3.7 kW induction motor (IM) with simulation and experiment. DTC is the most popular method to control the torque, speed, and stator current ripple of the induction motor as it overcomes the demerits of vector control by implementing the advanced control strategy. the conventional model of DTC using a proportional integral (PI) controller has low tracking performance with parameter changes, hence the analysis has been performed to suppress the ripple content of speed and torque by introducing a model predictive control scheme which is one of the latest and most popular techniques. Further, the network is properly trained with network parameters using an ant colony optimization algorithm so that the designed network can think from its intelligent data process and will set the required voltage vector for the three-phase inverter. Moreover, the MPC-ACO controller is verified and compared with the PI controller in many aspects such as steady-state analysis, dynamic response, and robustness study. therefore, torque and speed can be controlled with an acceptable limit and the desired dynamic performance is achieved with MPC-ACO controller by comparing with the PI controller as verified from simulation and experiment. © 2021 IEEE.

关键词： Model predictive control

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Traffic Signal control Based on Deep Reinforcement Learning with Simplified State and Reward Definitions 4

Traffic Signal Control Based on Deep Reinforcement Learning ...

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4th international conference on Artificial Intelligence and Big Data, ICAIBD 2021

作者： Bouktif, Salah Cheniki, Abderraouf Ouni, Ali El-Sayed, Hesham College of Information Technology University of United Arab Emirates Al Ain United Arab Emirates Institute of Electrical and Electronics Engineering University of Boumerdes Boumerdes Algeria École de Technologie Supérieure University of Quebec MontrealQC Canada

ISBN: (纸本)9780738131702

Traffic congestion has recently become a real issue especially within crowded cities and urban areas. Intelligent transportation systems (ITS) leveraged various advanced techniques aiming to optimize the traffic flow and subsequently alleviate the traffic congestion. In particular, traffic signal control TSC is one of the essential ITS techniques for controlling the traffic flow at intersections. Many research works have been proposed to develop algorithms and techniques which optimize TSC behavior. Recent works leverage Deep Learning (DL) and Reinforcement Learning (RL) techniques to optimize TSCs. However, most of Deep RL proposals are based on complex definitions of state and reward in the RL framework. In this work, we propose to use an alternative way of formulating the state and reward definitions. Basically, the basic idea is to define both state and reward in a simplified and straightforward manner rather than the complex design. We hypothesize that such a design approach simplifies the learning of the RL agent and hence provides a rapid convergence to optimal policies. For the agent architecture, we employ the double deep Q-Network (DDQN) along with prioritized experience replay (PER). We conduct the experiments using the Simulation of Urban MObility (SUMO) simulator interfaced with Python framework and we compare the performance of our proposal to traditional and learning-based techniques. © 2021 IEEE.

关键词： Reinforcement learning

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Resource Allocation for Edge Collaboration with Deep Deterministic Policy Gradient in Smart Railway 4

Resource Allocation for Edge Collaboration with Deep Determi...

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4th IEEE international conference on Electronics Technology, ICET 2021

作者： Chen, Yali Wu, Hao Beijing Jiaotong University School of Electronic and Information Engineering Beijing China Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety Beijing China

ISBN: (纸本)9781728176734

With the emergence of the streaming service and big data for smart railway, such as real-time ultrahigh definition video transmissions, the combination of Internet of things and edge computing is indeed one of the promising technologys to satisfy the high level requirement of the sixth generation wireless communication system, such as Gbit/s experience in high-speed railway (HSR) scene. However, due to the extreme complexity of joint optimization task offloading and resource allocation, and the demand for computing-constrained vehicular terminals of railway (VTR), it is urgent to introduce the mobile edge computing and resource allocation algorithms into intelligent railway systems. In this paper, we propose a deep deterministic policy gradient based edge collaboration resource allocation algorithm (DECRA). the proposed architecture can intelligently allocate edge computing resources and channel resources to achieve task offloading and computing migration. Numerical results demonstrate the effectiveness of the proposed DECRA algorithm, which achieves resource allocation smartly when the speed of the VTR is up to 240km/h, and makes DECRA practical for the HSR in the edge computing system. © 2021 IEEE.

关键词： Resource allocation

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A semantic segmentation method based on improved u-net network 4

A semantic segmentation method based on improved u-net netwo...

引用

4th international conference on advanced Electronic Materials, Computers and Software engineering, AEMCSE 2021

作者： Li, Penghui Zhang, Lijun Qiao, Jinlong Wang, Xiangguo China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan China

ISBN: (纸本)9781665415965

Semantic segmentation is the most important branch of image processing. Semantic segmentation based on deep learning occupies the mainstream method. CNN, FCN, U-NET and DEEPLAB series have achieved good results in the field of image semantic segmentation. the improvement methods of each network also emerge in an endless stream, but the emphasis of improving the network focuses on the feature transfer and feature fusion between network layers in each method. In this paper, based on u-net, we use deep convolution, residual autonomic force and dendrite network to improve the network model. Deep convolution can reduce the amount of calculation, deepen the depth of network, extract more abundant image information, and transmit information between network layers in a more refined way. Dendritic networks are different from ordinary neural networks. Ordinary neural networks process information as models of nerve cell bodies. the role of neural dendrites is also important in the process of information processing. Dendritic network is used as a model of neural dendrites to improve the ability of information processing. the improved network in this paper was tested on the VOC2012 dataset, and the experimental results showed that PA, mAP and IoU were 93.36%, 92.28% and 68.26% respectively. the experimental results showed that the improved network in this paper had improved in all indicators. © 2021 IEEE.

关键词： Semantic Segmentation

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Image segmentation of argon blowing based on improved Otsu algorithm 4

Image segmentation of argon blowing based on improved Otsu a...

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4th international conference on Intelligent Autonomous Systems (ICoIAS)

作者： Huang, Yukang Xiong, Ling Liu, Yang Deng, Pan Dan, Binbin Wuhan Univ Sci & Technol Engn Res Ctr Met Automat & Measurement Technol Inst Robot & Intelligent Syst Minist Educ Wuhan 430081 Peoples R China Wuhan Univ Sci & Technol Key Lab Met Equipment & Control Minist Educ Wuhan 430081 Peoples R China WISCO Ltd Technol Ctr Baosteel Cent Res Inst Wuhan 430081 Peoples R China

ISBN: (纸本)9781665441957

Argon blowing at the bottom of ladle is a process for smelting high-quality steel. For realizing the argon blowing automatic control of flow based computer vision, the argon blowing interface is monitored by a camera. Image segmentation of argon blowing is the key to get clear exposed area of molten steel. In order to ensure the accuracy and real-time of image segmentation, an improved Otsu algorithm is proposed. Firstly, the simulated annealing algorithm is adopted to optimum the new individual selection process of genetic Algorithm. then use the proportion of the target area pixels to the image as the weight to modify the formula of maximum interclass variance. Finally, the improved Otsu formula is used as the fitness function of the genetic algorithm for image thresholding. Experiments show that the proposed algorithm can achieve greater F-score than other algorithms, and the requirement of real-time image processing can be satisfied, which is valuable in engineering application.

关键词： image segmentation Otsu algorithm argon blowing image threshold

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A Defect Detection Method Based on Improved Mask R-CNN for Wafer Maps 4

A Defect Detection Method Based on Improved Mask R-CNN for W...

引用

4th international conference on Computer Network, Electronic and Automation, ICCNEA 2021

作者： Li, Yang Wang, Jianguo School Of Computer Science And Engineering Xian Technological University Xian China State And Provincial Joint Engineering Lab. Of Advanced Network Monitoring And Control Xian China

ISBN: (纸本)9781665444866

Pattern recognition of defects in wafer drawing is very important to determine the root cause of production defects, which can provide insights for the production improvement of wafer plants. In wafer manufacturing process, there will be mixed defects, detection of mixed defects is much more complex. Deep learning method has become a good choice to solve the problem of complex pattern recognition. In this paper, an improved Mask R-CNN model for wafer defect map is proposed. the ability of small target recognition is improved by fusing residual network and feature pyramid network, and the target feature can be fully extracted in the shallow model, so that the efficiency of feature extraction is improved. Secondly, an improved non-maximum suppression (NMS) algorithm is added to solve the error detection problem caused by traditional algorithms. the experimental results show that the improved Mask R-CNN model is superior to the conventional model, and has better recognition effect for small targets and shallow models. Secondly, the improved NMS algorithm is added to improve the detection precision. © 2021 IEEE.

关键词： Defects

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Inverse control optimization of voltage and temperature parameters of electric vehicle fuel cell based on genetic algorithm 4

Inverse control optimization of voltage and temperature para...

引用

4th IEEE international conference on Automation, Electronics and Electrical engineering, AUTEEE 2021

作者： Sun, Guizhi Song, Zhenquan Xi, Junhong Zhu, Liang Yantai Vacational College Shandong Yantai264670 China Yantai Star Auto Service Co.Ltd. Shandong Yantai264000 China

ISBN: (纸本)9781665428392

Fuel cell vehicle generally includes two power sources with different characteristics, fuel cell and auxiliary battery, which belong to series hybrid drive structure. the whole vehicle control strategy of fuel cell vehicle includes energy distribution strategy, brake feedback strategy and shift control strategy. A multi-input single-output fuzzy controller based on GA (Genetic Algorithm) is designed to solve the inverse control optimization problem of voltage and temperature parameters of electric vehicle fuel cell. the initial weights and thresholds of the neural network are optimized by using the strong global searching ability of GA, and then the best weights and thresholds are obtained by using the fast local searching speed of BPNN(BP neural network) algorithm. the simulation results show that the inverse control method can quickly and accurately decouple the voltage and temperature in the fuel cell, and ensure the performance requirements of the electric vehicle for the fuel cell. © 2021 IEEE.

关键词： Genetic algorithms

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Generalized VSG control Strategy for Active Power Transient Characteristic Optimization of Voltage Source Inverter 4

Generalized VSG Control Strategy for Active Power Transient ...

引用

4th IEEE China international Electrical and Energy conference, CIEEC 2021

作者： Huang, Xuezheng Chen, Changsong Hu, Wenhao Jiang, Mengjie Chen, Haowen Huazhong University of Science and Technology The State Key Laboratory of Advanced Electromagnetic Engineering and Technology Wuhan China

ISBN: (纸本)9781728171494

Both droop control and virtual synchronous generator (VSG) control can be widely seen used in voltage source inverter. Among them, the virtual inertia and damping characteristics VSG control has the ability to provide virtual inertia factors that droop control does not have, but its active power response speed is very slow, and there is a large overshoot. Aiming at the problem of poor active power transient characteristics of VSG control, a generalized VSG control strategy is proposed. First, the article analyzes the transient characteristics of the active power-frequency loop of droop control and VSG control, and derives the generalized VSG control strategy. then, according to the system model, the influence of the pole-zero point of the main controller of generalized VSG control strategy on the frequency response speed, the response speed and overshoot of active power is analyzed. And on this basis, a parameter design parameter design method is given, which can eliminate active power overshoot and make the active power response as fast as possible while keeping the frequency response speed unchanged. Finally, an inverter grid-connected bench was built to verify the effectiveness and feasibility of the proposed generalized VSG control strategy. © 2021 IEEE.

关键词： Electric inverters

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