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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Liu, Yajun Li, Ru Li, Aimin Fei, Rong Guo, Xie Wu, Fang-Xiang Xi'an University of Technology Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an China Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China University of Saskatchewan Division of Biomedical Engineering Department of Computer Science Department of Mechanical Engineering Saskatoon Canada

ISBN: (纸本)9798350337488

As the largest class of small non-coding RNAs, piRNAs primarily present in the reproductive cells of mammals, which influence post-transcriptional processes of mRNAs in multiple ways. Effective methods for predicting piRNA and mRNA target relationships can help identify piRNA functions, investigate the possibility of piRNAs as biomarkers and therapeutic targets. In this study, we propose a computational approach for classifying the relationships of piRNA-mRNA pairs based on an interactive inference network (IIN). First, we gather piRNA-mRNA target data, collect sequence data by position alignment, and construct a benchmark dataset. Furthermore, a reliable negative set is constructed by positive-unlabeled learning. Finally, we view a piRNA and a mRNA sequence as a premise and hypothesis sentence, respectively, and IIN model is used to predict the relationship between them. The experiments demonstrate that our method effectively characterizes piRNA-mRNA interaction and could be beneficial for researchers to investigate piRNA functions. © 2023 IEEE.

关键词： interactive inference network noncoding RNA piRNA-mRNA interactions positive-unlabeled learning

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Fast S-transform for fault line selection in distribution network system

Fast S-transform for fault line selection in distribution ne...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Jiao Shang-bin Yang Yun-peng Shi Yan-jin Shi Wen-wen Guo Jing-wen Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China

The current of the distribution networks under 66kV is widely operating in small current grounding mode. The problem of extracting the fault feature in each line would be quite difficult due to the short duration of the transient zero sequence current with the non-stationary and non-linear characteristics when the single-phase-to-ground fault occurs in the system. Therefore, a novel method of single-phase-to-ground fault line selection for small current based on Fast S-transform (FST) is developed in this paper. Firstly, FST is presented to transform the transient electric current signal in each feeder, after that the one-dimension modulus and phase angle value can been obtained. Then, the feeder with the largest energy value calculated by the modulus obtained above is selected as the alternative possible fault line. Finally, line failure or bus failure can been determined by evaluating the difference of the phase angle between the fault line and the comparison line that has been selected from the non-alternative feeders before. The results of the simulative and experimental circuits reveal that the proposed method using FST can avoid the influence of neural point grounding type. Additionally, the method of line selection is quite accurate and real-time.

关键词： Transient analysis Circuit faults Grounding Time-frequency analysis Feature extraction Fourier transforms

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Adaptive learning controller design for uncertain nonlinear active suspension system with actuator input delay and time-varying state constraints

Adaptive learning controller design for uncertain nonlinear ...

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第33届中国控制与决策会议

作者： Huijun Guo Jintao Liang Key Laboratory of Shaanxi Province for Complex System Control and Intelligent Information Processing Guilin University of Electronic Technology

This paper investigates the adaptive tracking control problem for active suspension system(ASS) with time-varying constraints via the neural network(NN) *** nonlinear terms in the spring and damper coefficients,input time delay of the actuator and the suspension performances are also considered *** NNs are used to approximate the unknown function caused by the uncertain car-body *** is known to all that ensuring the vertical displacement and speed states in the constraint regions can guarantee the stability and safety of the ***,by introducing the symmetric barrier lyapunov function from the time-varying constraints,an adaptive controller based on the NNs and nonlinear backstepping technique is developed to guarantee the states within *** the stability of the whole system,including the semi-global ultimately uniformly boundedness of the all signals of the ASSs,is analyzed by the Lyapunov stability ***,simulation results are provided to verify the feasibility of the adaptive learning controller.

关键词： Active suspension systems adaptive control input delay neural networks

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PLC based variable structure control of hydraulic position servo system considering controller saturation

PLC based variable structure control of hydraulic position s...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Hai-Peng Ren Xuan Wang Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian University of Technology Xian China

Due to the advantages of strong carrying capacity and fast response speed, hydraulic servo system has been widely used in industrial motion control field. The hydraulic servo system is susceptible to the nonlinearity, parameter uncertainty and unknown disturbance, which makes the high performance position control of the hydraulic servo system become a challenge. In this paper, considering the hydraulic position servo control system with input saturation, a sliding mode variable structure controller with shrinking boundary layer is designed. The proposed method is used to experimentally track three kinds of reference signals based on Programmable Logic controller (PLC), i.e., S7-200PLC, and hydraulic control system provided by Festo company. The experiment results indicate that the proposed method is effective and achieves smaller steady state tracking error as compared with sign function robust item and the conventional PID control.

关键词： Servomotors Cavity resonators Valves Force Touch sensitive screens

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Direct symbol decoding using GA-SVM in chaotic baseband wireless communication system

arXiv

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arXiv 2021年

作者： Yin, Hui-Ping Ren, Hai-Peng Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China

To retrieve the information from the serious distorted received signal is the key challenge of communication signal processing. The chaotic baseband communication promises theoretically to eliminate the inter-symbol interference (ISI), however, it needs complicated calculation, if it is not impossible. In this paper, a genetic algorithm support vector machine (GA-SVM) based symbol detection method is proposed for chaotic baseband wireless communication system (CBWCS), by this way, treating the problem from a different viewpoint, the symbol decoding process is converted to be a binary classification through GA-SVM model. A trained GA-SVM model is used to decode the symbols directly at the receiver, so as to improve the bit error rate (BER) performance of the CBWCS and simplify the symbol detection process by removing the channel identification and the threshold calculation process as compared to that using the calculated threshold to decode symbol in the traditional methods. The simulation results show that the proposed method has better BER performance in both the static and time-varying wireless channels. The experimental results, based on the wireless open-access research platform, indicate that the BER of the proposed GA-SVM based symbol detection approach is superior to the other counterparts under a practical wireless multipath channel. Copyright © 2021, The Authors. All rights reserved.

关键词： Bit error rate

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Fault diagnosis for small samples based on VMR

Fault diagnosis for small samples based on VMR

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2024 China Automation Congress, CAC 2024

作者： Wu, Xuejin Wu, Yali Hu, Yanghu Department of Information and Control Engineering Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an710048 China State Key Laboratoiy of Metal Extrusion and Forging Equipment Technology China National Heavy Machinery Research Institute Co. Ltd Xi'an710016 China

ISBN: (纸本)9798350368604

The scarcity of fault samples presents a significant challenge for fault diagnosis in industrial processes. Conventional methods often fail to deliver satisfactory results when dealing with small sample sizes. In addressing the issue of small sample fault diagnosis in industrial processes, this paper utilizes the Variational Mode Reconstruction(VMR) algorithm to screen the best components decomposed by the Variational Mode Decomposition(VMD) through the envelope entropy then random weighting them and signal reconstruction to achieve data enhancement, to enrich the sample size and to prevent the model overfitting phenomenon due to the scarcity of samples. Meanwhile, this paper integrates Convolutional Neural Network (CNN) and Long Short-term Memory Neural Network (LSTM) to propose a network model of spatio-temporal feature fusion for feature extraction and classification. The experiments demonstrate that this model not only enhances data diversity but also ensures consistency before and after enhancement, effectively mitigating overfitting. Furthermore, it guarantees high recognition and generalization rates in fault diagnosis. © 2024 IEEE.

关键词： Convolutional neural networks

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Grid-forming converters control based on DC voltage feedback

arXiv

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arXiv 2020年

作者： Gao, Yuan Ren, Hai-Peng Li, Jie Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’anShaanxi710048 China

The renewable energy is connected to the power grid through power electronic converters, which are lack of make the inertia of synchronous generator/machine (SM) be lost. The increasing penetration of renewable energy in power system weakens the frequency and voltage stability. The Grid-Forming Converters(GFCs) simulate the function of synchronous motor through control method in order to improve the stability of power grid by providing inertia and stability regulation mechanism. This kind of converter control methods include virtual synchronous machine, schedulable virtual oscillator control and so on. These control method mainly use AC side state feedback and do not monitor the DC side state. This paper analyzes the control strategy of GFC considering power grid stability, including Frequency Droop control, Virtual Synchronous Machine control and dispatchable Virtual Oscillator control. The DC side voltage collapse problem is found when a large load disturbance occurs. The control methods of GFC considering DC side voltage feedback are proposed, which can ensure the synchronization characteristics of grid connection and solve the problem of DC side voltage collapse. The proposed method is verified by IEEE-9 bus system, which shows the effectiveness of the proposed method. Copyright © 2020, The Authors. All rights reserved.

关键词： State feedback

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A Low-complexity Decision Variables Classification Brainstorm Optimization Algorithm

A Low-complexity Decision Variables Classification Brainstor...

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2024 International Conference on Applied Mathematics, Modelling and Statistics Application, AMMSA 2024

作者： Li, Qiyue Qiu, Lipeng Zhou, Aoran Wu, Yali Wang, Ziren Department of Information and Control Engineering Xi'An University of Technolog Xi'an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an710048 China State Key Laboratory of Metal Extrusion and Forging Equipment Technology China National Heavy Machinery Research Institute Co. Ltd. Xi'an710016 China

In the complex optimization scenarios of real life, we often need to not only weigh the conflicts between multi-objectives but also face the challenges brought by large-scale decision variables. When the scale of decision variables increases sharply, the search space will expand exponentially, which makes it difficult for the algorithm to traverse the whole search space under limited resources, so that the number of local optimal solutions increases sharply. The so-called 'dimension disaster' appears. To effectively deal with this problem, this paper proposes a large-scale multi-objective brainstorm optimization algorithm (LMaOBSO) based on low complexity decision variable classification method and improved penalty boundary intersection strategy. The algorithm uses a low-complexity tree sorting variable classification method to divide the decision variables into converges and diversity variables quickly. At the same time, the convergent variables are optimized by the improved penalty boundary crossover strategy to solve the problems existing in large-scale optimization problems. © Published under licence by IOP Publishing Ltd.

关键词： Disasters

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Distributed Secondary control of DC Microgrids with Operation Loss Reduction 43

Distributed Secondary Control of DC Microgrids with Operatio...

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43rd Chinese control Conference, CCC 2024

作者： Qiu, Maoxiang Zhang, Zhicheng Zuo, Zhiqiang Wang, Yijing Tianjin University Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin300072 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China

ISBN: (纸本)9789887581581

In DC microgrids, current sharing and voltage regulation are two main objectives for real-time control, while the operation loss reduction is typically achieved by steady-state optimization. However, the ratio of current sharing is generally determined by the result of the centralized optimization in the classical hierarchical control framework of DC microgrids. Such an issue brings insufficient capability in respond to the changes of photovoltaic power and stored energy in the solar-powered energy systems. To handle this, this work proposes a distributed control scheme for single-bus DC microgrids. Under the proposed controller, the objectives of current sharing, bus voltage regulation and the total operation loss (converter loss and line loss) reduction can be guaranteed simultaneously. Moreover, the constraints on line currents and bus voltage are tackled as well. Finally, simulations verify the performance of the proposed control scheme. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Microgrids

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State-of-Charge Balancing control for Battery Energy Storage systems of Near-Space Vehicles with an Electric-Thermal-Aging Coupling Model 42

State-of-Charge Balancing Control for Battery Energy Storage...

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42nd Chinese control Conference, CCC 2023

作者： Zuo, Zhiqiang Du, Yunhao Wang, Yijing Zhang, Zhicheng Li, Peng School of Electrical and Information Engineering Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System Tianjin University Tianjin300072 China Ministry of Education Key Laboratory of System Control and Information Processing Shanghai200240 China

ISBN: (纸本)9789887581543

State-of-charge (SoC) balancing is crucial for improving the efficiency and lifetime of the battery energy storage system in near-space vehicles. In this paper, the SoC balancing control problem is investigated by a coupling battery model with electric-thermal-aging dynamics. Firstly, a system identification experiment is carried out to obtain the internal parameters of the battery. Secondly, a weight optimization index is designed by integrating the balancing speed and battery state-of-health (SoH). Then, a receding horizon control algorithm is proposed to realize multi-unit battery SoC balancing with partial swarm optimization (PSO). Finally, the effectiveness of the proposed strategy is verified by simulation results. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Battery management systems

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