Huaqiang Zhang

Shandong University of Technology

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Mei Zhao

Harbin Institute of Technology

Xinsheng Wang

Harbin Institute of Technology

Yao Tong

University of Wisconsin–Madison

Yongsheng Chen

Nankai University

Yongxiang Xu

Harbin Institute of Technology

Dongxing Li

China Institute of Atomic Energy

Pingpeng Tang

Harbin Institute of Technology

Guangming Zheng

Shandong University of Technology

Liu Lingshun

Civil Aviation University of China

Chao Tong

Henan Agricultural University

Cooperative Institutions

Harbin Institute of Technology

Chinese Academy of Sciences

Shandong University of Technology

Henan Agricultural University

University of Chinese Academy of Sciences

Ministry of Education of the People's Republic of China

Wuhan University

Beijing Institute of Technology

Jilin University

Shandong University

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A High-Reliability Event-Triggered Secondary Control Strategy for Microgrid Considering Time-Varying Delay

IEEE Systems Journal (2022)

Jiancheng Zhang Huaqiang Zhang

A decentralized hierarchical control strategy with communication time-varying delay is designed for microgrid (MG) to enhance the voltage and frequency regulation. Recently, event-triggered consensus algorithm is used to reduce energy consumption. To improve the communication reliability, data loss due to communication interruption is considered in this article. First, each distributed generator (DG) of MG is regarded as an agent. Based on multiagent consistency theory, the distributed secondary controller is established. Second, the event trigger function of the secondary controller is constructed, and the stability of the secondary controller is proved by Lyapunov theorem. Third, a data predictive controller is established to train and learn the historical voltage, frequency, and active power of MG by using the improved extreme learning machine (ELM) algorithm. When communication is interrupted, the ELM controller is triggered and the lost data is compensated in time. Finally, the effectiveness of the control strategy is verified by simulation. Simulation results show that the proposed control strategy effectively adjusts the frequency and voltage, realizes accurate active power sharing, reduces the communication burden, and improves the reliability of MG.

Microgrid

10.1109/jsyst.2022.3156655

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Citations (12)

NIGWO-iCaps NN: A Method for the Fault Diagnosis of Fiber Optic Gyroscopes Based on Capsule Neural Networks

Micromachines (2025)

Nan Lu Huaqiang Zhang Chunmei Dong Hongtao Li Yu Chen

When using a fiber optic gyroscope as the core measurement element in an inertial navigation system, its work stability and reliability directly affect the accuracy of the navigation system. The modeling and fault diagnosis of the gyroscope is of great significance in ensuring the high accuracy and long endurance of the inertial system. Traditional diagnostic models often encounter challenges in terms of reliability and accuracy, for example, difficulties in feature extraction, high computational cost, and long training time. To address these challenges, this paper proposes a new fault diagnostic model that performs a fault diagnosis of gyroscopes using the enhanced capsule neural network (iCaps NN) optimized by the improved gray wolf algorithm (NIGWO). The wavelet packet transform (WPT) is used to construct a two-dimensional feature vector matrix, and the deep feature extraction module (DFE) is added to extract deep-level information to maximize the fault features. Then, an improved gray wolf algorithm combined with the adaptive algorithm (Adam) is proposed to determine the optimal values of the model parameters, which improves the optimization performance. The dynamic routing mechanism is utilized to greatly reduce the model training time. In this paper, effectiveness experiments were carried out on the simulation dataset and real dataset, respectively; the diagnostic accuracy of the fault diagnosis method in this paper reached 99.41% on the simulation dataset; the loss value in the real dataset converged to 0.005 with the increase in the number of iterations; and the average diagnostic accuracy converged to 95.42%. The results show that the diagnostic accuracy of the NIGWO-iCaps NN model proposed in this paper is improved by 13.51% compared with the traditional diagnostic methods. It effectively confirms that the method in this paper is capable of efficient and accurate fault diagnosis of FOG and has strong generalization ability.

Feature vector

10.3390/mi16010073

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Forsythiaside A attenuates mastitis via PINK1/Parkin-mediated mitophagy

Phytomedicine (2024)

Jingjing Liu Yingkui Gao Huaqiang Zhang Zhonghua Hao Guangwei Zhou

PINK1

10.1016/j.phymed.2024.155358

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Citations (4)

Analysis on Hinterland Segmentation in Port Project

International Conference on Engineering Computation (2009)

Jie Wang Huaqiang Zhang

Port is an important component of the transportation system; analysis of port hinterland scale is essential prerequisite and special requirement to port project. How to make quantitative analysis on hinterland with scientific theory model and method and how to determine the reasonable hinterland is critical, it is directly related to the success of port project. In order to improve the scientific and rationality of the present hinterland segmentation, the definition of hinterland is described and main influencing factors of port hinterland segmentation are listed at first in this paper. We make comparison between the common methods of present port hinterland segmentation, on this basis the gravitational model is mainly applied in hinterland segmentation, moreover empirically make analysis according to the actual situation of the adjacent TianJin port and QinDao port. Base on the analysis and study, the gravitational model can reflect more the practical hinterland segmentation, and more objective and more scientific support to port project.

Port (circuit theory)

10.1109/icec.2009.37

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Citations (3)

Marine Hybrid Power Drive System Based on Model Predictive Control

International Journal of Engineering Research and (2019)

Huaqiang Zhang

Marine Hybrid Power Drive System Based on Model Predictive Control - written by Huaqiang Zhang , Fengming Sun , Tong Yao published on 2019/06/01 download full article with reference data and citations

Model Predictive Control

Zhàng

Predictive power

10.17577/ijertv8is050332

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Citations (0)

T's Correlation Degree on Effect of Mooney Viscosity on Solution Polymerized Styrene-butadiene Rubber

Guangzhou Chemical Industry (2011)

Huaqiang Zhang

Using T's correlation degree theory,the effect of mooney viscosity on solution polymerized styrene-butadiene rubber(SSBR) was studied.Compose of butadiene and styrene,molecular weight and distributing of SSBR was the important influence of mooney viscosity,and its value was positive relativity.The vinyl(1,2-%)content,the random unit and impurity level of material was the subordination influence of mooney viscosity,and its value was minus relativity.

Mooney viscosity

Styrene-butadiene

Degree of polymerization

Degree (music)

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New Development of Wind Energy Generation and Control Strategy

Low Voltage Apparatus (2009)

Huaqiang Zhang

The development of wind energy generation,for example,larger rated power,offshore wind turbine generator system,VSCF,no gear-box driven,and construction design,remote wireless network wind farm monitoring system,was reviewed.The construction and theory of wind energy generation system,state monitoring system,testing parameters,system function were introduced.The power control strategies,such as pitch control,yaw control and generator control,were discussed,and LVRT was proposed.Analysis results show that MVSC-HVDC should be applied in the wind farm,because of its quick response and efficient control result.

Pitch control

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Citations (4)

Cooperative-PSO-based PID neural network integral control strategy and simulation research with asynchronous motor controller design

WSEAS Transactions on Circuits and Systems archive (2009)

Piao Haiguo Zhixin Wang Huaqiang Zhang

This paper focuses on the design of robustness controller for asynchronous motor. a new PID neural network-integral (PIDNN-I) synthesis control strategy is proposed for the controller design, in which NARMA-L2, an approximated model of nonlinear auto regressive moving average(NARMA) model, is employed to represent the input-output behavior of the motor and gives out the expected control input. PID neurons network (PIDNN), as a kind of novel neural network model with dynamic characteristics, is adopted in NARMA-L2 to identify the motor. PIDNN integrates the advantages of PID with those of artificial neuron network. However, the conventional back-propagation (BP) algorithm, which easily gets trapped in local minimum and is being adopted in the current model, constrains the identifying ability of PIDNN so as to harm to the completion of the controller design. Particle swarm optimization (PSO) algorithm, a new population-based evolutionary global optimization method, is proposed to replace the BP algorithm to train the neurons model. Cooperative particle swarm optimization (CPSO), an improved version of cooperative random learning particle swarm optimization (CRPSO), is put forward to enhance the performances of the conventional PSO in the design. Due to the existence of the tracking error caused by approximate error between identifying and real system, integral (I) control is introduced into the design, namely adopting PIDNN control in large tracking error scale and PIDNN-I control in small tracking error scale. Compared with conventional PID control strategy, simulation results demonstrate that the CPSO-based PIDNN-I synthesis control strategy has improved the control performances of asynchronous motor in robustness and accuracy efficiently.

Robustness

Tracking error

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Citations (11)

Research of GPS receiver hardware scheme based on C674X

Electronic Design Engineering (2011)

Huaqiang Zhang

In this paper,a GPS hardware circuit diagram is elaborated,the diagram take the GP2015 and the GP2021 chip set of Zarlink company as the nucleus frame,take C6747 as the related calculator,well considering low-power,high performance and small encapsulation,which are requested in the shell environment;take the familiar arithmetic of signal quickly undertaking as the foundation,it presents the core flow chart of the GPS position software;finally after completing the hardware and the arithmetic designs,an examination of the translating of the navigation code is carried.

Calculator

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Distributed finite‐time cooperative control of droop‐controlled microgrids under switching topology

IET Renewable Power Generation (2016)

Xinsheng Wang Huaqiang Zhang Changxi Li

As a small-scale power system, microgrid (MG) will lose support from the main grid if it switches to islanded mode because of the pre-planned scheduling or unplanned disturbances. To synchronise the frequency and voltage to their reference values, a secondary frequency and voltage cooperative control is proposed in this study. The proposed secondary control can synchronise the frequency and voltage to their reference values in finite time and achieve the active power sharing simultaneously. Moreover, it is suitable for switching communication architecture. The MG is considered as multi-agent systems and the system stability is proved by multi-agent theory and finite-time stability theory. A simulation system is established in Matlab/Simulink environment, and the results show the effectiveness of the proposed controller.

Microgrid

10.1049/iet-rpg.2016.0526

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Citations (55)