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International Conference on Intelligent Transportation

作者： Zixuan Zhang Yuan Cao Shuai Su Junlin Zhang Wei Wang School of Electric and Information Engineering Beijing Jiaotong University Beijing China State Key Laboratory of Rail Traffic Control and Safety and the Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing China Traffic Control Technology Co. Ltd Beijing China Department of Automation Traffic Control Technology Co. Ltd Tsinghua University Beijing China

The integrated control of separated power electric multiple units (EMUs) and cars is a significant research field, the cars cooperative control problem of the separated power EMUs is investigated in this paper. Firstly, assuming that the separated power EMUs are composed of different numbers of powered cars and trailer cars connected by elastic couplers, and considering the electric traction/braking force, air braking force, and nonlinear basic resistance, a multi-particle model is established. Then a novel cost function is designed considering speed and position tracking errors, in-train force, traction energy consumption, and regenerative energy. Based on the model predictive control (MPC) methodology, a cooperative control approach is proposed to optimize the operation performance of separated power EMUs. The proposed control approach can improve EMUs tracking accuracy, and reduce internal force and net energy consumption during EMUs operation. Finally, the proposed approach is verified by numerical simulations.

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A Dual-Optimization Fault Diagnosis Method For Rolling Bearing Based On Hierarchical Slope Entropy And SVM Synergized with Shark Optimization Algorithm

SSRN

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SSRN 2022年

作者： Li, Yuxing Tang, Bingzhao Huang, Bo Jiao, Shangbin Xue, Xiaohui School of Automation and Information Engineering Xi’an University of Technology Xi’an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China

Slope entropy (SlopEn) has been widely applied in fault diagnosis and has performed excellent performance, while SlopEn suffers from the problem of thresholds selection. Aim to further enhance the identifying capability of SlopEn in fault diagnosis, on basis of the SlopEn, the concept of hierarchy is combined and proposed new complexity feature, namely hierarchical slope entropy (HSlopEn). Meanwhile, the white shark optimizer (WSO) is applied to optimize the both HSlopEn and support vector machine (SVM), and WSO-HSlopEn and WSO-SVM are proposed respectively. Then, a dual-optimization fault diagnosis method for rolling bearing based on WSO-HSlopEn and WSO-SVM is put forward. Firstly, different types of bearing signals are input and decomposed into several nodes by hierarchical decomposition. Then taking the recognition rate as the fitness function, the parameters of HSlopEn and SVM are determined adaptively by WSO. After that, the WSO-HSlopEn of the nodes are extracted and single-feature and multi-features extraction are performed. Finally, the diagnosis results are output by WSO-SVM. Experimental results demonstrated that whether under single-feature or multi-features, based on WSO-HSlopEn and WSO-SVM fault diagnosis method has the highest recognition rate compared to other hierarchical entropies;moreover, under multi-features, the recognition rates are all higher than 97.5%, and the more features we select, the better the recognition effect will be. when five nodes are selected, the highest recognition rate reaches 100%. © 2022, The Authors. All rights reserved.

关键词： Support vector machines

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HRPose: Real-Time High-Resolution 6D Pose Estimation Network Using Knowledge Distillation

arXiv

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arXiv 2022年

作者： Guan, Qi Sheng, Zihao Xue, Shibei Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

Real-time 6D object pose estimation is essential for many real-world applications, such as robotic grasping and augmented reality. To achieve an accurate object pose estimation from RGB images in real-time, we propose an effective and lightweight model, namely High-Resolution 6D Pose Estimation Network (HRPose). We adopt the efficient and small HRNetV2-W18 as a feature extractor to reduce computational burdens while generating accurate 6D poses. With only 33% of the model size and lower computational costs, our HRPose achieves comparable performance compared with state-of-the-art models. Moreover, by transferring knowledge from a large model to our proposed HRPose through output and feature-similarity distillations, the performance of our HRPose is improved in effectiveness and efficiency. Numerical experiments on the widely-used benchmark LINEMOD demonstrate the superiority of our proposed HRPose against state-of-the-art methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Distillation

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Capacity Optimization of a Hybrid Energy Storage system Considering Wind-Solar Reliability Evaluation Based on a Novel Multi-Strategy Snake Optimization Algorithm

SSRN

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SSRN 2022年

作者： Wang, Chen Jiao, Shangbin Li, Yujun Zhang, Qing School of Automation and Information Engineering Xi’an University of Technology Xi’an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China

When the capacity configuration of a hybrid energy storage system (HESS) is optimized considering the reliability of a wind turbine and photovoltaic generator (PVG), the sequential Monte Carlo method is typically adopted to simulate the normal operation and fault probability of wind turbines and PVG units. The capacity optimization configuration model of the HESS is constructed with the life cost cycle (LCC) as an objective and the loss of power supply probability (LPSP) as constraints. The variational mode decomposition is used to decompose the unbalanced power in the wind-PV microgrid. The maximum power of the optimized the battery bank and the supercapacitor bank are used to determine the frequency division point, and the high-frequency power and low-frequency power are respectively allocated to the supercapacitor bank and the battery bank. When the snake optimizer (SO) is used to solve the nonconvex capacity optimization configuration model of the HESS, poor accuracy and stability are significant problems. The opposition-based learning, adaptive weight factor, and Lévy flight strategy are introduced in the algorithm framework. Twenty-three test functions show that multi strategy snake optimizer (MSO) significantly improves the accuracy and convergence speed compared with SO. Nine optimization algorithms including MSO are used to solve the capacity optimization problem of the HESS. The results show that MSO is superior to other algorithms in performance and numerical accuracy. It can reduce the LCC 4.5% and ensure that the capacity of the HESS meets the load demand when the wind turbine and PVGs are in a fault state. © 2022, The Authors. All rights reserved.

关键词： Variational mode decomposition

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How to Share: Balancing Layer and Chain Sharing in Industrial Microservice Deployment

arXiv

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arXiv 2022年

作者： Liu, Yuxiang Yang, Bo Wu, Yu Chen, Cailian Guan, Xinping Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

With the rapid development of smart manufacturing, edge computing-oriented microservice platforms are emerging as an important part of production control. In the containerized deployment of microservices, layer sharing can reduce the huge bandwidth consumption caused by image pulling, and chain sharing can reduce communication overhead caused by communication between microservices. The two sharing methods use the characteristics of each microservice to share resources during deployment. However, due to the limited resources of edge servers, it is difficult to meet the optimization goals of the two methods at the same time. Therefore, it is of critical importance to realize the improvement of service response efficiency by balancing the two sharing methods. This paper studies the optimal microservice deployment strategy that can balance layer sharing and chain sharing of microservices. We build a problem that minimizes microservice image pull delay and communication overhead and transform the problem into a linearly constrained integer quadratic programming problem through model reconstruction. A deployment strategy is obtained through the successive convex approximation (SCA) method. Experimental results show that the proposed deployment strategy can balance the two resource sharing methods. When the two sharing methods are equally considered, the average image pull delay can be reduced to 65% of the baseline, and the average communication overhead can be reduced to 30% of the baseline. Copyright © 2022, The Authors. All rights reserved.

关键词： Production control

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Train Safety control Based on Deep Deterministic Policy Gradient with control Barrier Function

Train Safety Control Based on Deep Deterministic Policy Grad...

引用

IEEE International Conference on Networking, Sensing and control

作者： Guoteng Wang Jidong Lv Hongjie Liu Ming Chai Tao Tang Wentao Zhang School of Automation and Intelligence Beijing Jiaotong University Beijing China National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University Beijing China State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong University Beijing China Beijing Zhengshi Environmental Engneering Company Beijing China

ISBN: (数字)9798350365221

ISBN: (纸本)9798350365238

Train Relative Distance Braking Mode (RDBM) has great potential to increase line capacity by enabling shorter following distances based on train-to-train communication in-formation. However, it is difficult for traditional train control methods to ensure avoidance of potential collision risks in RDBM while dealing with the nonlinearity and uncertainty of train dynamics. In this paper, a novel train safety control method combining Deep Deterministic Policy Gradient (DDPG) and control Barrier Function(Cbf)is proposed. Firstly, the safety constraint set for adjacent trains, considering their braking capabilities, is analyzed, and the uncertainty of train dynamics is modeled using a Gaussian process. Secondly, DDPG is used to explore the optimal control strategy under the action of uncertain train dynamics, and CBF provides compensation control input to ensure safety during the learning process. Then, a DDPG-CBF algorithm is presented to achieve efficient safety controller design and implementation. Finally, sufficient numerical simulations demonstrate that, compared with DDPG algorithm alone, the DDPG-CBF algorithm can not only ensure the safe and stable operation of trains, but also learn train control strategies expe-ditiously and accurately under different operating environments, with an average efficiency increase of 38.94 %.

关键词： Rails Uncertainty Heuristic algorithms Process control Optimal control Numerical simulation Stability analysis Safety Sensors Numerical stability

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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 ...

引用

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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A Mixed Integer Linear Programming Model for the Distribution of Transport Tasks Among Heterogeneous Robots in a Factory

A Mixed Integer Linear Programming Model for the Distributio...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Igor Pardal Latini Wilson Eduardo Barioni Marco Teixeira Flavio Neves-Jr Lucia Valeria Ramos de Arruda CPGEI-UTFPR Curitiba Parana Brazil Universidade Tecnologica Federal do Parana (UTFPR) Curitiba Parana Brazil Automation and Advanced Control System Laboratory (LASCA) Graduate Program in Electrical and Computer Engineering (CPGEI) Pontificia Universidade Catolica do Parana (PUCPR) Curitiba Parana Brazil PPGla-PUCPR Curitiba Parana Brazil

ISBN: (数字)9798350340266

ISBN: (纸本)9798350340273

The growing need for automation of factories and their processes determines a constant increase in the use of robots to carry out various tasks. Multiple robots can do different tasks simultaneously, speeding up processes. This practice raises the question of how many robots are needed to service the entire process, given all the limitations of the operation. One of these limitations is due to the navigation systems used by the several robots in the environment. Line-followers robots, for example, can only meet some tasks but are cheaper than free-movement ones. In this work, we develop an optimization model for task allocation among the available robots to minimize execution delays using mixed integer linear programming, considering their navigation systems. With the model, it is possible to obtain the best task allocation for each robot and the order to perform such tasks, thus avoiding delays as much as possible and getting zero delays for the presented case, that emulates the process of a vehicle assembler factory line.

关键词： Service robots Navigation Search problems Production facilities Delays Mixed integer linear programming Batteries

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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...

引用

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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