检索结果-内蒙古大学图书馆

6th International Conference on Intelligent control, measurement and Signal Processing, ICMSP 2024

作者： Yu, Pingyang Liu, Yanping Wan, Defu Yao, Xue The College of Electronic Engineering Xi'an Shiyou University Dept. of Measurement and Control Technology and Instrument China

ISBN: (纸本)9798331516550

This paper mainly introduces an optimized matching pursuit algorithm for the reconstruction of seismic reflection events. It adopts intelligent optimization algorithms of genetic algorithm (GA) and particle swarm algorithm (PSO) to matching pursuit algorithm for improving the processing effect and efficiency. Through experiments on synthetic seismic records and field seismic data, it demonstrates that both GA-MP and PSO-MP can reconstruct the reflection events effectively and efficiency, while PSO-MP performs better especially in waveform reconstruction. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

来源：评论

学校读者我要写书评

暂无评论

The Reconstruction of Seismic Reflection Events by Optimized Matching Pursuit Algorithm

The Reconstruction of Seismic Reflection Events by Optimized...

引用

Intelligent control, measurement and Signal Processing and Intelligent Oil Field (ICMSP), International Conference on

作者： Pingyang Yu Yanping Liu Defu Wan Xue Yao Dept. of Measurement and Control Technology and Instrument The College of Electronic Engineering of Xi’an Shiyou University

ISBN: (数字)9798331516550

ISBN: (纸本)9798331516567

关键词： Seismic measurements Matching pursuit algorithms Signal processing algorithms Process control Reflection Frequency measurement Noise measurement Particle swarm optimization Frequency control Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Self-Powered Dust Removal System for Solar Panels Driven by a Rotary Freestanding-Electret Generator 22

Self-Powered Dust Removal System for Solar Panels Driven by ...

引用

22nd International Conference on Solid-State Sensors, Actuators and Microsystems, Transducers 2023

作者： Ding, Rong Teng, Junchi Cao, Zeyuan Wu, Zibo Deng, Kang Yuan, Xiangzhu Cao, Yujia Ye, Xiongying Tsinghua University State Key Laboratory Of Precision Measurement Technology And Instruments Dept. Of Precision Instrument Beijing100084 China

ISBN: (纸本)9784886864352

As an important renewable energy, solar power generation is faced with the issue that dust accumulation will block the sunlight and reduce power efficiency. This paper reports a self-power dust removal system for solar panels, based on dielectric electrophoresis driven by a rotary freestanding electret generator that harvests wind energy. The system directly uses the output electrode of the solar panel as one of the electrodes of the dust removal unit, and doesn't affect the output performance of the panel. In a demonstration, two dust removal units can be driven by one generator under the slow wind of 1.6 m/s, and the dust on two solar panels was effectively removed and the output of the panels was recovered to 97% and 98%, respectively. © 2023 IEEJ.

关键词： Dust removal electret generator energy harvesting solar panels wind energy

来源：评论

学校读者我要写书评

暂无评论

Compressed Gridless Frequency Estimation by Segmented Atomic Norm Minimization for Random Demodulation 16

Compressed Gridless Frequency Estimation by Segmented Atomic...

引用

16th IEEE International Conference on Electronic measurement and instruments, ICEMI 2023

作者： Fan, Meiyu Han, Bingtong Zhang, Jingchao Qiao, Liyan Harbin Institute of Technology Dept. Automatic Test and Control Harbin China Beijing Institute of Radio Measurement Beijing China

ISBN: (纸本)9798350327144

The fixed-dictionary based gridded frequency sparse representation in random demodulation systems faces the grid mismatch problem, which may lead to severe degradation of the compression algorithm to the extent that high precision signal parameters and signal reconstruction cannot be obtained. Gridless compressed sensing introduces the concept of atomic norm, which solves the grid problem caused by spectrum discretization and greatly improves the accuracy of signal frequency estimation. However, in practice, solving large-scale meshless compressed sensing problems directly can consume a lot of time and storage resources. In this paper, we borrow the idea of segmented random sampling to compress the signal by generating segmented pseudo-random sequences in a random demodulation system. Then each segment of the compressed sampled signal is reconstructed and frequency estimated by atomic norm separately, and the obtained frequency estimates of several segments are averaged to obtain the frequency estimates of the original signal. The algorithm can achieve a recovery signal-to-noise ratio of 68 dB for a signal with 256 points per segment, and the recovery accuracy is only related to the number of points within the segment, independent of the number of segments. The algorithm reduces the computational complexity and improves the solution size and the accuracy of frequency estimation. © 2023 IEEE.

关键词： Demodulation

来源：评论

学校读者我要写书评

暂无评论

Self-Powered Dust Removal System for Solar Panels Driven by a Rotary Freestanding-Electret Generator

Self-Powered Dust Removal System for Solar Panels Driven by ...

引用

International Conference on Solid State Sensors and Actuators (TRANSDUCERS)

作者： Rong Ding Junchi Teng Zeyuan Cao Zibo Wu Kang Deng Xiangzhu Yuan Yujia Cao Xiongying Ye Dept. of Precision Instrument State Key Laboratory of Precision Measurement Technology and Instruments Tsinghua University Beijing China

As an important renewable energy, solar power generation is faced with the issue that dust accumulation will block the sunlight and reduce power efficiency. This paper reports a self-power dust removal system for solar panels, based on dielectric electrophoresis driven by a rotary freestanding electret generator that harvests wind energy. The system directly uses the output electrode of the solar panel as one of the electrodes of the dust removal unit, and doesn’t affect the output performance of the panel. In a demonstration, two dust removal units can be driven by one generator under the slow wind of 1.6 m/s, and the dust on two solar panels was effectively removed and the output of the panels was recovered to 97% and 98%, respectively.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Computationally Efficient Predictive control Based on ANN State-Space Models

Computationally Efficient Predictive Control Based on ANN St...

引用

IEEE Conference on Decision and control

作者： Jan H. Hoekstra Bence Cseppento Gerben I. Beintema Maarten Schoukens Zsolt Kollár Roland Tóth Dept. of Electrical Engineering at the Eindhoven Control Systems group University of Technology The Netherlands Dept. of Measurement and Information Systems Budapest University of Technology and Economics Hungary Institute for Computer Science and Control Budapest Hungary

Artificial neural networks (ANN) have been shown to be flexible and effective function estimators for the identification of nonlinear state-space models. However, if the resulting models are used directly for nonlinear model predictive control (NMPC), the resulting nonlinear optimization problem is often overly complex due to the size of the network, requires the use of high-order observers to track the states of the ANN model, and the overall control scheme does not exploit the available autograd tools for these models. In this paper, we propose an efficient approach to auto-convert ANN statespace models to linear parameter-varying (LPV) form and solve predictive control problems by successive solutions of linear model predictive problems, corresponding to quadratic programs (QPs). Furthermore, we show how existing deep-learning methods, such as SUBNET that uses a state encoder, enable efficient implementation of MPCs on identified ANN models. Performance of the proposed approach is demonstrated by a simulation study on an unbalanced disc system.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Computationally efficient predictive control based on ANN state-space models

arXiv

引用

arXiv 2023年

作者： Hoekstra, Jan H. Cseppento, Bence Beintema, Gerben I. Schoukens, Maarten Kollár, Zsolt Tóth, Roland Dept. of Measurement and Information Systems The Budapest University of Technology and Economics Hungary The Dept. of Electrical Engineering The Eindhoven University of Technology Netherlands Institute for Computer Science and Control Budapest Hungary

Artificial neural networks (ANN) have been shown to be flexible and effective function estimators for identification of nonlinear state-space models. However, if the resulting models are used directly for nonlinear model predictive control (NMPC), the resulting nonlinear optimization problem is often overly complex due the size of the network, requires the use of high-order observers to track the states of the ANN model, and the overall control scheme exploits little of the structural properties or available autograd tools for these models. In this paper, we propose an efficient approach to auto-convert ANN state-space models to linear parameter-varying (LPV) form and solve predictive control problems by successive solutions of linear model predictive problems, corresponding to quadratic programs (QPs). Furthermore, we show how existing ANN identification methods, such as the SUBNET method that uses a state encoder, can provide efficient implementation of MPCs. The performance of the proposed approach is demonstrated via a simulation study on an unbalanced disc system. © 2023, CC BY-SA.

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

Compressed Gridless Frequency Estimation by Segmented Atomic Norm Minimization for Random Demodulation

Compressed Gridless Frequency Estimation by Segmented Atomic...

引用

International Conference on Electronic measurement and instruments, ICEMI

作者： Meiyu Fan Bingtong Han Jingchao Zhang Liyan Qiao Dept. Automatic Test and Control Harbin Institute of Technology Harbin China Beijing Institute of Radio Measurement Beijing China

关键词：

来源：评论

学校读者我要写书评

暂无评论

Performance Evaluation of State and Output Feedback-based Repetitive controllers for Rotational control Systems

Performance Evaluation of State and Output Feedback-based Re...

引用

International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET)

作者： Akif Rahmatillah Edi Kurniawan Aulia Siti Aisjah Katherin Indriawati Dept. of Engineering Physics Faculty of Industrial Technology & Systems Engineering Sepuluh Nopember Institut of Technology Surabaya Indonesia Research Group of Precision Control & Measurement Research Centre for Photonics National Research and Innovation Agency Tangerang Selatan Indonesia

ISBN: (数字)9798350389920

ISBN: (纸本)9798350389937

This study examines the tracking performance of state and output feedback-based repetitive controllers (RCs) for rotational control systems. First, a state feedback RC is designed in the time domain using a state-space model, which requires full state information for implementation. The state feedback RC is modeled as a 2D hybrid system, where the control and learning actions can be designed independently using Linear Matrix Inequality (LMI) solutions. This approach is evaluated on a rotational control system expressed as a strictly proper linear system with a relative degree of 1. Second, for comparison, an output feedback RC, also known as a general RC, is designed for the same system. Numerical experiment results show that while the state feedback RC achieves lower peak and root-means-quare errors, it exhibits slower transient response compared to the output feedback RC.

关键词： Microwave antennas State feedback Transient response Velocity control control systems Radar antennas Telecommunications Time-domain analysis Output feedback Convergence

来源：评论

学校读者我要写书评

暂无评论

An Application of a Wiener Filtering Based on Short Time Spectrum Estimation for High Frequency Seismic Signal Processing 12

An Application of a Wiener Filtering Based on Short Time Spe...

引用

12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019

作者： Liu, Yanping Yan, Zhengguo College of Electronic Engineering of Xi'an Shiyou University Dept. of Measurement and Control Technology and Instrument China Key Laboratory of Oil and Gas Well Measurement Control Technology in Shaanxi Xi'an China

ISBN: (纸本)9781728148526

This paper introduces a Wiener filtering method based on short time spectrum estimation which is implemented in frequency domain and applied to process seismic signals of high frequency. Since many seismic signal filtering methods could preserve the valid information of middle and low frequency well but could not preserve the valid information of high frequency well, so it needs to adopt a method which could preserve both low and high frequency of seismic signal. The Wiener filtering is the optimal filtering in the sense of minimum mean square error, and the way of frequency domain implementation is simpler and more effective than time domain implementation. So, it adopts Wiener filtering of frequency domain in this paper to obtain better results in seismic signal processing than conventional filtering method of time domain such as Kalman filtering, especially for high frequency seismic signals. © 2019 IEEE.

关键词： Mean square error

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：