This page has only limited features, please log in for full access.

Unclaimed
Ming Lu
School of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan, China

Basic Info

Basic Info is private.

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Original paper
Published: 25 July 2021 in Nonlinear Dynamics
Reads 0
Downloads 0

In this paper, distributed output feedback consensus tracking control of multiple nonholonomic mobile robots with sensor faults and communication through a directed graph is studied. In the presence of sensor faults, the main challenge to achieve distributed consensus tracking control lies in that both individual position measurements and relative position between one robot and its neighbors are faulty. To address this issue, an adaptive-based output feedback scheme which involves estimator, observer and controller design is proposed. In the proposed control scheme, a fully distributed estimator is constructed to estimate the reference trajectory for each robot to avoid utilizing the faulty relative position variable. Based on the information from the estimator, an adaptive observer-based output feedback controller is designed to compress the effects of sensor faults and realize trajectory tracking for each robot. It is shown that the boundedness of all the signals in the resulting closed-loop system can be guaranteed, and the consensus tracking error of the system can converge to an adjustable neighborhood of zero by appropriately choosing design parameters even in the presence of sensor faults. Simulation results are provided to verify the effectiveness of the proposed scheme.

ACS Style

Ying Zou; Chao Deng; Ming Lu. Distributed output feedback consensus tracking control of multiple nonholonomic mobile robots with directed communication graphs and sensor faults. Nonlinear Dynamics 2021, 105, 2327 -2339.

AMA Style

Ying Zou, Chao Deng, Ming Lu. Distributed output feedback consensus tracking control of multiple nonholonomic mobile robots with directed communication graphs and sensor faults. Nonlinear Dynamics. 2021; 105 (3):2327-2339.

Chicago/Turabian Style

Ying Zou; Chao Deng; Ming Lu. 2021. "Distributed output feedback consensus tracking control of multiple nonholonomic mobile robots with directed communication graphs and sensor faults." Nonlinear Dynamics 105, no. 3: 2327-2339.

Research article
Published: 26 May 2021 in Security and Communication Networks
Reads 0
Downloads 0

The traditional malicious uniform resource locator (URL) detection method excessively relies on the matching rules formulated by the network security personnel, which is hard to fully express the text information of the URL. Thus, an improved multilayer recurrent convolutional neural network model based on the YOLO algorithm is proposed to detect malicious URL in this paper. First, single characters are mapped to dense vectors using word embedding, and the dense vectors are participated in the training process of the whole model according to the structural characteristics of the URL in the method. Then, the CSPDarknet neural network model based on the improved YOLO algorithm is proposed to extract features of the URL. Finally, the extracted features are used to evaluate malicious URL by the bidirectional LSTM recurrent neural network algorithm. In order to verify the validity of the algorithm, a total of 200,000 URLs are collected, including 100,000 normal URLs labeled “good” and 100,000 malicious URLs labeled “bad”. The experimental results show that the method detects malicious URLs more quickly and effectively and has high accuracy, high recall rate, and high accuracy compared with Text-RCNN, BRNN, and other models.

ACS Style

Zuguo Chen; Yanglong Liu; Chaoyang Chen; Ming Lu; Xuzhuo Zhang. Malicious URL Detection Based on Improved Multilayer Recurrent Convolutional Neural Network Model. Security and Communication Networks 2021, 2021, 1 -13.

AMA Style

Zuguo Chen, Yanglong Liu, Chaoyang Chen, Ming Lu, Xuzhuo Zhang. Malicious URL Detection Based on Improved Multilayer Recurrent Convolutional Neural Network Model. Security and Communication Networks. 2021; 2021 ():1-13.

Chicago/Turabian Style

Zuguo Chen; Yanglong Liu; Chaoyang Chen; Ming Lu; Xuzhuo Zhang. 2021. "Malicious URL Detection Based on Improved Multilayer Recurrent Convolutional Neural Network Model." Security and Communication Networks 2021, no. : 1-13.

Conference paper
Published: 06 October 2020 in Advances in Intelligent Systems and Computing
Reads 0
Downloads 0

The survey found that during table tennis training there are often many scattered balls that need to be picked up manually, affecting the efficiency of the players’ training. Currently, table tennis is picked up manually using a table tennis picker. In this paper, delta omnidirectional wheeled table tennis automatic pickup robot based on the vision servo achieves fully automatic table tennis pickup by combining the characteristics and requirements of table tennis sports. In this paper, we design a vision algorithm for a table tennis automatic pickup robot system, give a kinematic inverse solution for the delta omnidirectional wheel, complete the design of the robot control system, and build the platform for the experiment. A pickup experiment is conducted on scattered ping-pong balls of different colors. Experiments have shown that the robot can safely clean up scattered table tennis balls on the table tennis field with high positioning accuracy and top pick up rate. It is proved that the robot designed in this paper has extensive application value and prospects.

ACS Style

Ming Lu; Cheng Wang; Jinyu Wang; Hao Duan; Yongteng Sun; Zuguo Chen. Delta Omnidirectional Wheeled Table Tennis Automatic Pickup Robot Based on Vision Servo. Advances in Intelligent Systems and Computing 2020, 537 -542.

AMA Style

Ming Lu, Cheng Wang, Jinyu Wang, Hao Duan, Yongteng Sun, Zuguo Chen. Delta Omnidirectional Wheeled Table Tennis Automatic Pickup Robot Based on Vision Servo. Advances in Intelligent Systems and Computing. 2020; ():537-542.

Chicago/Turabian Style

Ming Lu; Cheng Wang; Jinyu Wang; Hao Duan; Yongteng Sun; Zuguo Chen. 2020. "Delta Omnidirectional Wheeled Table Tennis Automatic Pickup Robot Based on Vision Servo." Advances in Intelligent Systems and Computing , no. : 537-542.

Journal article
Published: 01 October 2020 in Information Sciences
Reads 0
Downloads 0

Considering the multi-feature fusion via information synergy entropy (ISE) based interval intuitionistic fuzzy (IIF) technique for order preference by similarity to ideal solution, the paper propose a method to identify the operating condition identification in a complex environment. In this method, the evaluation information contained in the decision matrices is characterized by an IIF number, and the related attribute weights are incompletely known. First, the ISE concept is proposed to calculate the weight of each attribute value which is used to construct a weighted collective decision matrix. Both intuitionistic and fuzzy information are incorporated into the matrix to describe the uncertainty in the IIF sets to improve the decision accuracy. Next, an improved Euclidean distance is used to calculate the degree of relative closeness so as to rank the decision alternatives, which can overcome the drawback of division by zero. Then the superheat identification is used as a case study to illustrate optimal operating condition determination of aluminium electrolysis cell. Experimental results have demonstrated the validity and applicability of the proposed operating condition determination algorithm.

ACS Style

Zuguo Chen; Ming Lu; Yimin Zhou; Chaoyang Chen. Information synergy entropy based multi-feature information fusion for the operating condition identification in aluminium electrolysis. Information Sciences 2020, 548, 275 -294.

AMA Style

Zuguo Chen, Ming Lu, Yimin Zhou, Chaoyang Chen. Information synergy entropy based multi-feature information fusion for the operating condition identification in aluminium electrolysis. Information Sciences. 2020; 548 ():275-294.

Chicago/Turabian Style

Zuguo Chen; Ming Lu; Yimin Zhou; Chaoyang Chen. 2020. "Information synergy entropy based multi-feature information fusion for the operating condition identification in aluminium electrolysis." Information Sciences 548, no. : 275-294.

Research article
Published: 28 July 2020 in Complexity
Reads 0
Downloads 0

After fault occurs, the fault diagnosis of wind turbine system is required accurately and quickly. This paper presents a fault diagnostic method for open-circuit faults in the converter of permanent magnet synchronous generator drive for the wind turbine. To avoid misjudgement or missed judgement caused by improper thresholds, the proposed method applies Local Mean Decomposition and Multiscale Entropy into the converter of wind power system fault diagnosis for the first time. This paper uses a novel multiclass support vector machine to classify the faults hardly diagnosed by other methods. Simulation results show that the method has the characteristics of high adaptability, high accuracy, and less diagnosis time.

ACS Style

Hao Duan; Ming Lu; Yongteng Sun; Jinyu Wang; Cheng Wang; Zuguo Chen. Fault Diagnosis of PMSG Wind Power Generation System Based on LMD and MSE. Complexity 2020, 2020, 1 -11.

AMA Style

Hao Duan, Ming Lu, Yongteng Sun, Jinyu Wang, Cheng Wang, Zuguo Chen. Fault Diagnosis of PMSG Wind Power Generation System Based on LMD and MSE. Complexity. 2020; 2020 ():1-11.

Chicago/Turabian Style

Hao Duan; Ming Lu; Yongteng Sun; Jinyu Wang; Cheng Wang; Zuguo Chen. 2020. "Fault Diagnosis of PMSG Wind Power Generation System Based on LMD and MSE." Complexity 2020, no. : 1-11.

Research article
Published: 24 July 2020 in Complexity
Reads 0
Downloads 0

Energy management strategy (EMS) is a key issue for hybrid energy storage system (HESS) in electric vehicles. By innovatively introducing the current speed information, the vehicle speed optimized fuzzy energy management strategy (VSO-FEMS) for HESS is proposed in this paper. Firstly, the pruned fuzzy rules are formulated by the SOC change of battery and super-capacitor to preallocate the required power of vehicle. Then, the real-time vehicle speed is used to optimize the pre-allocated results based on the principle of vehicle dynamics, so as to realize the optimal allocation of required power. To validate the proposed VSO-FEMS strategy for HESS, simulations were done and compared with other EMSs under the typical urban cycle in China (CYC-CHINA). Results show that the final SOC of battery and super-capacitor are optimized in varying degrees, and the total energy consumption under the VSO-FEMS strategy is 2.43% less than rule-based strategy and 1.28% less than fuzzy control strategy, which verifies the effectiveness of the VSO-FEMS strategy.

ACS Style

Xizheng Zhang; Zhangyu Lu; Ming Lu. Vehicle Speed Optimized Fuzzy Energy Management for Hybrid Energy Storage System in Electric Vehicles. Complexity 2020, 2020, 1 -12.

AMA Style

Xizheng Zhang, Zhangyu Lu, Ming Lu. Vehicle Speed Optimized Fuzzy Energy Management for Hybrid Energy Storage System in Electric Vehicles. Complexity. 2020; 2020 ():1-12.

Chicago/Turabian Style

Xizheng Zhang; Zhangyu Lu; Ming Lu. 2020. "Vehicle Speed Optimized Fuzzy Energy Management for Hybrid Energy Storage System in Electric Vehicles." Complexity 2020, no. : 1-12.

Conference paper
Published: 01 July 2020 in Proceedings of the 2nd International Conference on Data Engineering and Communication Technology
Reads 0
Downloads 0

Trend analysis, a database method for condition identification, is widely used in engineering. The sliding window method is an important method for trend analysis. However, the original sliding window method uses an invariant preset threshold and a fixed initial window, which will lead to inaccurate segmentation and long processing time. To solve this problem, it is a reasonable choice to improve the original scheme with dynamic threshold and dynamic initial window. In this paper, a trend extraction method based on improved sliding window is proposed, which can extract the trend characteristics of variables accurately and quickly.

ACS Style

Ming Lu; Yongteng Sun; Hao Duan; Zuguo Chen. A Trend Extraction Method Based on Improved Sliding Window. Proceedings of the 2nd International Conference on Data Engineering and Communication Technology 2020, 415 -422.

AMA Style

Ming Lu, Yongteng Sun, Hao Duan, Zuguo Chen. A Trend Extraction Method Based on Improved Sliding Window. Proceedings of the 2nd International Conference on Data Engineering and Communication Technology. 2020; ():415-422.

Chicago/Turabian Style

Ming Lu; Yongteng Sun; Hao Duan; Zuguo Chen. 2020. "A Trend Extraction Method Based on Improved Sliding Window." Proceedings of the 2nd International Conference on Data Engineering and Communication Technology , no. : 415-422.

Journal article
Published: 07 June 2020 in Minerals Engineering
Reads 0
Downloads 0

Rougher flotation is a complex process, making it difficult for a single variable to comprehensively and accurately reflects real-time working conditions. This paper proposes a new multivariable recognition method for rougher flotation conditions using pulp flow and froth size as parameters. It utilizes qualitative trend analysis to recognise rougher flotation condition for the first time, where an improved trend extraction method is used to improve extraction accuracy, and fuzzy logic is adopted to calculate the matching degree of trends. Considering the change in knowledge base caused by the increase in variables, this paper presents a scheme of building knowledge base for multivariable rougher flotation conditions. Experimental results of gold–antimony rougher flotation show that the proposed method can accurately recognise rougher flotation conditions.

ACS Style

Ming Lu; Yongteng Sun; Hao Duan; Dongheng Xie; Zuguo Chen; Jinyu Wang; Cheng Wang. A working condition recognition method based on multivariable trend analysis for gold–antimony rougher flotation. Minerals Engineering 2020, 156, 106493 .

AMA Style

Ming Lu, Yongteng Sun, Hao Duan, Dongheng Xie, Zuguo Chen, Jinyu Wang, Cheng Wang. A working condition recognition method based on multivariable trend analysis for gold–antimony rougher flotation. Minerals Engineering. 2020; 156 ():106493.

Chicago/Turabian Style

Ming Lu; Yongteng Sun; Hao Duan; Dongheng Xie; Zuguo Chen; Jinyu Wang; Cheng Wang. 2020. "A working condition recognition method based on multivariable trend analysis for gold–antimony rougher flotation." Minerals Engineering 156, no. : 106493.

Review
Published: 24 October 2019 in Applied Sciences
Reads 0
Downloads 0

This review introduces some energy-saving technologies of wastewater treatment. This work can provide some help for those who are engaged in energy conversation and energy efficiency research of wastewater treatment.

ACS Style

Yongteng Sun; Ming Lu; Yongjun Sun; Zuguo Chen; Hao Duan; Duan Liu. Application and Evaluation of Energy Conservation Technologies in Wastewater Treatment Plants. Applied Sciences 2019, 9, 4501 .

AMA Style

Yongteng Sun, Ming Lu, Yongjun Sun, Zuguo Chen, Hao Duan, Duan Liu. Application and Evaluation of Energy Conservation Technologies in Wastewater Treatment Plants. Applied Sciences. 2019; 9 (21):4501.

Chicago/Turabian Style

Yongteng Sun; Ming Lu; Yongjun Sun; Zuguo Chen; Hao Duan; Duan Liu. 2019. "Application and Evaluation of Energy Conservation Technologies in Wastewater Treatment Plants." Applied Sciences 9, no. 21: 4501.