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Acta Mathematica Scientia 2023年第3期43卷 1031-1044页

作者：刘振海 Nikolaos S.PAPAGEORGIOU Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big Data Processing Yulin Normal UniversityYulin537000China Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis Guangxi Minzu UniversityNanning530006China Department of Mathematics National Technical UniversityZografou Campus15780AthensGreece

We study a double phase Dirichlet problem with a reaction that has a parametric singular term. Using the Nehari manifold method, we show that for all small values of the parameter, the problem has at least two positiv... 详细信息

关键词： double phase singular term unbalanced growth Musielak-Orlice spaces Nehari manifold positive solutions

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Fault diagnosis of bearings based on deep separable convolutional neural network and spatial dropout

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Chinese Journal of Aeronautics 2022年第10期35卷 301-312页

作者： Jiqiang ZHANG Xiangwei KONG Xueyi LI Zhiyong HU Liu CHENG Mingzhu YU School of Mechanical Engineering and Automation Northeastern UniversityShenyang 110819China Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of EducationNortheastern UniversityShenyang 110819China Liaoning Province Key Laboratory of Multidisciplinary Design Optimization of Complex Equipment Northeastern UniversityShenyang 110819China Angang Steel Company Limited Anshan 114021China

Bearing pitting,one of the common faults in mechanical systems,is a research hotspot in both academia and *** fault diagnosis methods for bearings are based on manual experience with low diagnostic *** study proposes a novel bearing fault diagnosis method based on deep separable convolution and spatial dropout *** separable convolution extracts features from the raw bearing vibration signals,during which a 3×1 convolutional kernel with a one-step size selects effective features by adjusting its *** similarity pruning process of the channel convolution and point convolution can reduce the number of parameters and calculation quantities by evaluating the size of the weights and removing the feature maps of smaller *** spatial dropout regularization method focuses on bearing signal fault features,improving the independence between the bearing signal features and enhancing the robustness of the model.A batch normalization algorithm is added to the convolutional layer for gradient explosion control and network stability *** validate the effectiveness of the proposed method,we collect raw vibration signals from bearings in eight different health *** experimental results show that the proposed method can effectively distinguish different pitting faults in the bearings with a better accuracy than that of other typical deep learning methods.

关键词： Batch normalization Convolutional neural network Fault diagnosis Similarity pruning Spatial dropout

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ANISOTROPIC(p,q)-EQUATIONS WITH COMPETITION PHENOMENA

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Acta Mathematica Scientia 2022年第1期42卷 299-322页

作者： Zhenhai LIU Nikolaos S.PAPAGEORGIOU Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big Data Processing Yulin Normal UniversityYulin 537000China Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis Guangxi University for NationalitiesNanning 530006China Department of Mathematics National Technical UniversityZografou Campus15780 Athens.Greece

We consider a nonlinear Robin problem driven by the anisotropic(p,q)-Laplacian and with a reaction exhibiting the competing effects of a parametric sublinear(concave) term and of a superlinear(convex) *** prove a bifurcation-type theorem describing the changes in the set of positive solutions as the parameter *** also prove the existence of a minimal positive solution and determine the monotonicity and continuity properties of the minimal solution map.

关键词： concave-convex nonlinearities anisotropic operators regularity theory maximum principle minimal positive solution

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Forming Circle Formations of Multi-agent systems Under Actuator Faults 5th

Forming Circle Formations of Multi-agent Systems Under Actu...

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5th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2021

作者： Liu, Jiajun Ru, Xinfeng Xia, Weiguo Wang, Chen China National Aeronautical Radio Electronic Research Institute and National Key Laboratory of Science and Technology on Avionics System Integration Shanghai China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education and School of Control Science and Engineering Dalian University of Technology Dalian China National Engineering Research Center of Software Engineering and the State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing China

ISBN: (纸本)9789811939976

A distributed fault-tolerant formation control law is designed in this paper for multi-agent systems under external disturbances and actuator faults including time-varying loss of effectiveness faults. The initial position of each agent is already on a circle and the control purpose is to form a desired formation on this circle. Based on this local information, a distributed adaptive formation control law is designed by employing the congelation of variables method to deal with time-varying actuator faults. Finally, a simulation example is given to verify the effectiveness of the adaptive fault-tolerant control design method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multi agent systems

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Application of PID parameters optimization based on GWO in mould level system

Application of PID parameters optimization based on GWO in m...

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2021 International Conference on Internet, Education and Information Technology, IEIT 2021

作者： Sitong, Liu Xiangwei, Kong Peifeng, Hao Hezhan, Gao Software College Northeastern University Shenyang China School of Mechanical Engineering Automation Northeastern University Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education Liaoning Province Key Laboratory of Multidisciplinary Design Optimization of Complex Equipment Shenyang China

ISBN: (纸本)9781665425636

Mold level stability is a very important factor in the continuous casting process. To effectively control the liquid level at the set value, solve the problems of disturbance, nonlinearity, and time-varying in the system, as well as modeling difficulties caused by uncertain factors, and aiming at the shortcomings of conventional PID control, the gray wolf algorithm is introduced the gray wolf optimization algorithm is used to self-tune the PID parameters, and the objective function is constructed based on the adjustment time and steady-state error of the mold liquid level system. Finally, the simulation and experimental results show that the algorithm optimization proposed in this paper is compared with the particle swarm algorithm, and the step response of the system is smoother. Gray Wolf optimized PID control has a fast response speed, with an adjustment time of 3.87s, which is lower than 13.46s for conventional PID control and 5.58s for the PSO algorithm. It can significantly improve the control accuracy and other performance indicators of the system. It provides a reference for improving the level control of the continuous casting mold. © 2021 IEEE.

关键词： Three term control systems

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PID Parameter optimization of Secondary Cooling Water Distribution Model for Continuous Casting Based on Improved Artificial Bee Colony Algorithm 4

PID Parameter Optimization of Secondary Cooling Water Distri...

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4th International Conference on Artificial Intelligence and Big Data, ICAIBD 2021

作者： Wang, Yibing Kong, Xiangwei Hao, Peifeng Software College Northeastern University Shenyang China School of Mechanical Engineering Automation Liaoning Province Key Laboratory of Multidisciplinary Design Optimization of Complex Equipment Northeastern University Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education Shenyang China

ISBN: (纸本)9780738131702

Dynamic control of secondary cooling in continuous casting is the key technology to improve the quality and efficiency of the slab. In order to improve the quality and efficiency of the slab, a new control strategy of secondary cooling water distribution based on an improved artificial bee colony algorithm is proposed. Based on the traditional artificial bee colony algorithm, adding the learning factor to the optimal individual learning factor and random individual of the current population and integrating the output overshoot mechanism into the objective function is effective to avoid the great overshoot phenomenon caused by the abruptly change of casting speed and the large fluctuation of casting surface temperature. The transfer function was constructed based on the coupling relationship between the distribution of secondary cooling water and slab surface temperature. The Simulink simulation model was established, which was compared with the PSO-DSWPI Method and conventional PID controller. The results showed that the improved artificial bee colony algorithm has a more minor error, higher control accuracy and more smooth step response, which provided a new method for realizing more accurate control of secondary cooling dynamic water distribution and had practical significance for improving slab quality. © 2021 IEEE.

关键词： Cooling water

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Few-shot Learning for Rolling Bearing Fault Diagnosis Based on Residual Convolutional Neural Network 4

Few-shot Learning for Rolling Bearing Fault Diagnosis Based ...

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4th International Conference on Artificial Intelligence and Big Data, ICAIBD 2021

作者： Cui, Zihao Kong, Xiangwei Hao, Peifeng Software College Northeastern University Shenyang China School of Mechanical Engineering Automation Liaoning Province Key Laboratory of Multidisciplinary Design Optimization of Complex Equipment Northeastern University Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education Shenyang China

ISBN: (纸本)9780738131702

This paper proposes a new Siamese network model for fault diagnosis with limited training samples. We introduce residual blocks to the Siamese network model for few-shot learning. By using the same or different types of sample pairs to learn, our model further improves the accuracy of the Siamese network in bearing fault diagnosis under different workloads and noisy environments. Experiments on the CWRU and MFPT data set showed that the proposed model outperforms the convolutional Siamese network in bearing fault diagnosis. The accuracy of our model has achieved more than 93% accuracy with 90 training samples on the CWRU and MFPT data set. All our models and experiments are available from https://***/WunaiDczh/Few_data_Learing. © 2021 IEEE.

关键词： Failure analysis

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Bayesian optimization Framework for Efficient Fleet design in Autonomous Multi-Robot Exploration

arXiv

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arXiv 2024年

作者： Concha, David Molina Li, Jiping Yin, Haoran Park, Kyeonghyeon Lee, Hyun-Rok Lee, Taesik Sirohi, Dhruv Lee, Chi-Guhn The Dynamic Optimization and Reinforcement Learning Laboratory The Department of Mechanical & Industrial Engineering University of Toronto TorontoONM5S3G8 Canada The Department of Electrical & Computer Engineering University of Toronto TorontoONM5S3G8 Canada The Division of Engineering Science The Faculty of Applied Science and Engineering University of Toronto TorontoONM5S3G8 Canada The Complex System Design Laboratory The Department of Industrial and Systems Engineering Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of The Department of Industrial Engineering Inha University Incheon22212 Korea Republic of

This study addresses the challenge of fleet design optimization in the context of heterogeneous multi-robot fleets, aiming to obtain feasible designs that balance performance and costs. In the domain of autonomous multi-robot exploration, reinforcement learning agents play a central role, offering adaptability to complex terrains and facilitating collaboration among robots. However, modifying the fleet composition results in changes in the learned behavior, and training multi-robot systems using multi-agent reinforcement learning is expensive. Therefore, an exhaustive evaluation of each potential fleet design is infeasible. To tackle these hurdles, we introduce Bayesian optimization for Fleet design (BOFD), a framework leveraging multiobjective Bayesian optimization to explore fleets on the Pareto front of performance and cost while accounting for uncertainty in the design space. Moreover, we establish a sub-linear bound for cumulative regret, supporting BOFD’s robustness and efficacy. Extensive benchmark experiments in synthetic and simulated environments demonstrate the superiority of our framework over state-of-the-art methods, achieving efficient fleet designs with minimal fleet evaluations. Copyright © 2024, The Authors. All rights reserved.

关键词： Multipurpose robots

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An overview of the robust approaches applied for 2D visual servoing

An overview of the robust approaches applied for 2D visual s...

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Hajer Abidi Hassen Mekki Khaled Kaâniche Mohamed Chtourou Intelligent Control design and Optimization of complex system (ICOS) University of Sfax Tunisia

In this paper we present an overview of recent robust approaches which aim 2D visual servoing systems. Since Visual servoing has been considered as a very effective technique for positioning and tracking functionalities, its main goal was to find good selections of visual data in order to be injected in a closed-loop. To guarantee the visual servoing robustness, it is important to alter many techniques like extraction, matching, tracking and path planning. The robustness depends on the error minimization which means the ability to resist severe outliers and to analyze confidence in each feature. Thereby, we can accomplish a better control and an accurate robotic task.

关键词： Visual servoing Robustness Cameras Visualization Trajectory

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Modular ultrasonic sensor platform for mobile robot

Modular ultrasonic sensor platform for mobile robot

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International Conference on Renewable Energies and Vehicular Technology (REVET)

作者： Imen Maâlej Mohamed Ouali Nabil Derbel ENIS Research Unit on Intelligent Control design & Optimisation of complex Systems (ICOS) University of Sfax Tunisia Computer and Embedded Systems Algeria ICOS: Research Unit on Intelligent Control Design and Optimization of Complex System Tunisia

The ultrasonic sensor is the most replied sensor in mobile robot to get environmental information and avoid obstacles. In fact, this type of sensors offers satisfactory results with affordable cost. However, one sensor is insufficient for a better perception of the environment. In this paper we opt for the conception of an ultrasonic sensor network to extract as much information as possible for measuring the distance between the robot and the obstacle. The algorithm for distance calculation is based on the measurement of the time of flight for the ultrasonic wave. The experimental results show a good performance of the conceived system for the distinction between different shapes of obstacles.

关键词： Acoustics Robot sensing systems Microcontrollers Shape Ultrasonic variables measurement Transmitters Shape measurement

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