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Gain-phase Error Self-calibration DOA Estimation Method Based on Sparse Bayesian 6

Gain-phase Error Self-calibration DOA Estimation Method Base...

引用

6th IEEE International Conference on Electronic information and Communication technology, ICEICT 2023

作者： Jin, Xu Wang, Xuhu Hou, Yujun Tian, Yu School of Information and Control Engineering Qingdao University of Technology Qingdao China

ISBN: (纸本)9798350399059

To estimate direction-of-arrival (DOA) in the case of coherent signals with unknown gain-phase errors, a gain-phase error self-calibration DOA estimation method based on sparse Bayesian is presented in this paper. Firstly, the decoherence is realized by the unitary transformation of the extended received data matrix. And then an off-grid SBL model with gain-phase error is proposed by vectorizing the covariance matrix obtained after the transformation and introducing the off-grid model into it. Finally, sparse Bayesian learning is combined to obtain the true DOA. Simulation results demonstrate that the proposed method provides improved performance in terms of both estimation accuracy and angular resolution over the most traditional compressed sensing method. © 2023 IEEE.

关键词： Direction of arrival

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TCR Self-Calibration System for Electrically Heated Tobacco Products 6

TCR Self-Calibration System for Electrically Heated Tobacco ...

引用

6th IEEE International Conference on Electronic information and Communication technology, ICEICT 2023

作者： Hu, Ke Fu, Xiangyu Wang, Kaikai Li, Yansheng School of Information and Control Engineering Qingdao University of Technology Qingdao China

ISBN: (纸本)9798350399059

An adaptive temperature coefficient of resistance (TCR) calibration scheme is proposed in this paper. The aim is to address temperature control errors caused by TCR of heating elements, in the heater of electrically heated tobacco products (eHTP). Data on the resistance and temperature of the heating element are collected. The adaptive scheme and a direct fitting scheme are executed based on the data obtained. Comparing the temperature control effect of the two schemes, it can be found that those two schemes have similar temperature control accuracy. The results show that the proposed scheme maintains temperatures within ± 3°C of the target, and the direct fitting scheme can control the temperatures within ± 2°C of the target. Finally, a physical test is carried out. The adaptive scheme can meet the expected criteria for TCR calibration and temperature control effects. © 2023 IEEE.

关键词： Tobacco

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Credit Risk Prediction Network Based on Semantic Feature Transformer and CNN 6

Credit Risk Prediction Network Based on Semantic Feature Tra...

引用

6th IEEE International Conference on Electronic information and Communication technology, ICEICT 2023

作者： Wang, Mengyuan Zhou, Lijian Meng, Qingyu Kong, Yifan Sun, Jie School of Information and Control Engineering Qingdao University of Technology Qingdao China

ISBN: (纸本)9798350399059

Credit risk is one of the main risks faced by financial institutions. Establishing credit risk prediction model is an important means to help financial institutions avoid risks and reduce losses. To fully extract the feature information in the credit data and improve the parallel computing capability of the model while reducing the network size, a credit risk prediction network based on semantic feature Transformer and CNN is proposed in this paper. Firstly, a Semantic Feature Transformer (SFTransformer) module is constructed by introducing semantic features into Transformer to extract credit risk features. Secondly, because one-dimensional convolutional neural network (1DCNN) has good feature extraction ability and parallel computing ability, the 1DCNN module is combined with the SFTransformer module to build a parallel network CNN-SFTransformer. Finally, the feature data of the borrower is fed into the CNN-SFTransformer model to calculate whether the borrower has default risk. In this paper, two real credit datasets from Australia and German in the UCI database are used for experiments. AUC and KS, two commonly used evaluation indicators, are used to evaluate the predictive performance of the model. Experimental results show that the CNN-SFTransformer model proposed in this paper has good performance in the task of credit risk prediction, with high accuracy and reliability. © 2023 IEEE.

关键词： Semantics

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Reinforcement Learning-based Frequency control for Renewable Energy Microgrids 7

Reinforcement Learning-based Frequency Control for Renewable...

引用

7th International Conference on Intelligent Robotics and control engineering, IRCE 2024

作者： He, Jing Zhang, Junpeng Jiang, Haiping Ma, Zongfang College of Information and Control Engineering Xi'an University of Architecture and Technology The Moe Key Laboratory of Intelligent Network and Network Security Xi'an Jiaotong University China Xi'an University of Architecture and Technology College of Information and Control Engineering Xi'an China

ISBN: (纸本)9798350352399

With extensive access to renewables, the inertia of microgrid is significantly reduced, which in turn puts forward higher requirements for the frequency stability of the system. In this paper, a frequency control method based on reinforcement learning is proposed for the intermittent and unstable characteristics of renewables. First, the microgrid frequency control principle and reinforcement learning theory are introduced. On this basis, a microgrid frequency control strategy based on Q-learning algorithm is proposed, and the design process is described in detail, including the design of the action set, state set, and reward function. Finally, the Q-learning algorithm is pretrained offline through simulation experiments, and tested in several scenarios for online operation. The effectiveness and adaptability of the proposed algorithm are verified through comparative analysis with other strategies. © 2024 IEEE.

关键词： Adversarial machine learning

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Energy Management Strategy based Charging Coordination for Electric Vehicle Integrated Distribution Grid

Energy Management Strategy based Charging Coordination for E...

引用

2023 International Conference on Future Energy Solutions, FES 2023

作者： Faghihi, Tayebeh Sabzi, Shahab Vajta, Laszlo Budapest University of Technology and Economics Department of Control Engineering and Information Technology Budapest Hungary

ISBN: (纸本)9798350332308

This paper proposes a smart charging coordination strategy for electric vehicles (EVs) in a low-voltage (LV) distribution network. The strategy employs an energy management approach that considers the price sensitivity of EV drivers. Three priority groups are specified based on the EV's state of charge (SoC) level: high-priority, low-priority, and normal-priority. Different time slots for charging are offered to drivers at varying prices, designated as red, blue, and green time zones. The proposed approach begins with a power flow program that checks all constraints before an EV can be permanently placed on a charging node. An objective function is formulated to minimize production costs while ensuring that the constraints on bus voltages and maximum allowed power consumption are met. Simulation results demonstrate the validity of the proposed algorithm in shifting loads while satisfying all network and EV constraints. © 2023 IEEE.

关键词： Electric vehicles

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Parallel Operation control Strategy of High-Frequency-Link Single-Phase Full Bridge Full Wave Inverter Based on Virtual Impedance

Parallel Operation Control Strategy of High-Frequency-Link S...

引用

2023 China Automation Congress, CAC 2023

作者： Zhu, Wenjie Li, Yunfei Li, Xuewu Lin, Xumei Sun, Yu Li, Shuo Zhang, Wenshuo School of Information and Control Engineering Qingdao University of Technology Qingdao China

ISBN: (纸本)9798350303759

The high-frequency-link single-phase full bridge full wave inverter with bidirectional active clamp circuit can realize safe commutation, and the secondary side of the transformer has no voltage spike. However, the capacity of a single high-frequency inverter is limited, and it cannot run for a long time at high load, which is difficult to meet the requirements of high-power applications. In this paper, a droop control strategy based on virtual impedance is established to realize the parallel operation of two high-frequency-link single-phase full-bridge full-wave inverters, which effectively improves the system capacity, and optimizes the circuit topology by simplifying the clamp circuit, and realizes the elimination of voltage spikes. The employment of virtual impedance improves the performance of the parallel system, and effectively solves the problem that the reactive power of the parallel system of inverters with different capacities is excessive and difficult to balance. Finally, through matlab/simulink simulation, the effectiveness of the droop control based on virtual impedance in the parallel operation of high-frequency- link single-phase full-bridge full-wave inverter is verified. © 2023 IEEE.

关键词： Reactive power

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A Stock Prediction Method Based on Singular Spectrum Analysis and Long Short-Term Memory Network 6

A Stock Prediction Method Based on Singular Spectrum Analysi...

引用

6th IEEE International Conference on Electronic information and Communication technology, ICEICT 2023

作者： Tang, Futong Yi, Hongjie Cui, Huijing Zhang, Ke School of Information and Control Engineering Qingdao University of Technology Qingdao China

ISBN: (纸本)9798350399059

There are lots of noise influence in stock price time series. Therefore, A stock prediction method based on Singular Spectrum Analysis (SSA) and Long Short-Term Memory network (LSTM) is proposed. SSA is used for stock time series denoising since it is appropriate to the nonlinear data denoising. The stock price prediction is realized using LSTM since it can effectively solve the problem of gradient explosion existing in traditional neural networks. To highlight the performance of SSA-LSTM, other different denoising methods are considered: Move Average filtering (MA), Median Filtering (MD) and Locally Weighted Scatterplot Smoothing (LOWESS). Meanwhile, the processed data obtained preprocessed by MA, MD and LOWESS are sent into Back Propagation network (BP), BP network optimized by Genetic Algorithm (GABP), Long Short-Term Memory network (LSTM) and Convolutional Neural Network (CNN) for comparison seperately. Mean Square Error (MSE) and coefficient of determination (R2) are used to evaluate the predicted performance. The experimental results show that the proposed SSA-LSTM has the highest accuracy for stock price prediction. © 2023 IEEE.

关键词： Long short-term memory

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LPV state-feedback control of a robotic manipulator via LMI optimization 29

LPV state-feedback control of a robotic manipulator via LMI ...

引用

29th International Conference on information, Communication and Automation Technologies, ICAT 2023

作者： Teczely, Zoltan Kiss, Balint Budapest University of Technology and Economics Department of Control Engineering and Information Technology Budapest Hungary

ISBN: (纸本)9798350399837

This paper presents an LPV model-based controller synthesis case study on a 2-DOF robotic manipulator. A polytopic LPV formulation was chosen with two scheduling variables. An H ∞ control strategy was used for the reference tracking objective which was implemented through LMI optimization and was compared to a nominal H∞ controller and feedback linearization extended with PD reference tracking criterion. The solution was tested on a real-life robotic arm located at BME Robotics Laboratory. Numerical evaluation was based on a joint measure of performance and robustness. © 2023 IEEE.

关键词： Feedback linearization

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PD control and the unwinding effect in quaternion parameterized attitude control 27

PD control and the unwinding effect in quaternion parameteri...

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27th IEEE International Conference on Intelligent engineering Systems, INES 2023

作者： Kimathi, Stephen Lantos, Bela Budapest University of Technology and Economics Department of Control Engineering and Information Technology Budapest Hungary

ISBN: (纸本)9798350328516

The unit quaternion is popular in the representation and control of rigid body attitude systems. However, it is known that two equilibrium points in the unit quaternion attitude formulation represent a single equilibrium point in a rotation matrix in SO(3). This often leads to a non-efficient control effort as the quaternion transients can settle to either of the equilibrium point regardless of the path taken or, even undergo a homoclinic orbit between the two equilibrium points. This behaviour is referred to as the unwinding effect. This paper presents solutions to cure the unwinding effect in unit quaternion parameterized attitude control systems through the use of a switching parameter or a saturation function. © 2023 IEEE.

关键词： Attitude control

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An Adaptive control Method Based on Radial Basis Function Neural Network for Variable Stiffness Actuator 25

An Adaptive Control Method Based on Radial Basis Function Ne...

引用

25th IEEE International Conference on Industrial technology, ICIT 2024

作者： Wu, Xiujun Wang, Chen Xu, Changxian Liu, Keping Wang, Gang Sun, Zhongbo Changchun University Of Technology Department Of Control Science And Engineering Changchun China School Of Electrical And Information Engineering Jilin Engineering Normal University Department Of Control Science And Engineering Changchun China

ISBN: (纸本)9798350340266

Rehabilitation robots based on variable stiffness elastic actuators exhibit strong human-robot interaction char-acteristics due to the specific features of the actuators, including flexible drive and variable stiffness output capabilities. However, to ensure the robot can achieve rehabilitation actions smoothly, safely, and precisely, accurate modeling and control of the variable stiffness elastic actuators becomes a burning question. In order to address this challenge, a dynamic model is established considering the actuator's own gravity factor and the influence of disturbances, and a nominal dynamic model is designed. Accurate tracking of output location and stiffness is reached by designing a radial basis function (RBF) network to approximate the actual dynamic model. Through simulation experiments, it is verified that the block approximation RBF network adaptive controller designed in this article has lower actuator tracking error and higher control accuracy than the proportional integral derivative (PID) controller. © 2024 IEEE.

关键词： Radial basis function networks

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