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TechRxiv 2023年

作者： Yang, Songnan Zhang, Xiaohui Liu, Ding Bai, Wenqi Liu, Fan The School of Automation and Information Engineering Xi’an University of Technology Shaanxi 710048 China The Institute of Advanced Navigation and Electromagnetics Xi’an University of Technology Shaanxi 710048 China The State Key Laboratory of Eco-Hydraulics in the Northwest Arid Region of China Xi’an University of Technology Shaanxi 710048 China The Shaanxi Key Laboratory of Complex System Control with the Intelligent Information Processing Xi’an University of Technology Shaanxi 710048 China

Numerous studies have demonstrated that numerous animal species are capable of goal-directed navigation using environmental information for dead reckoning. The stable magnetic field of the earth provides important information for the migration of animals over long distances. Inspired by the goal-directed navigation of animals, a novel Geomagnetic Navigation with Temporal Attention-based Data-Driven Dead Reckoning (Attention-DR) method for Autonomous Underwater Vehicles (AUV) is presented in this article, which only utilizes the inclination angle (I) and the declination angle (D) of the Geomagnetic Field (GF) for underwater navigation without any prior knowledge of the geographical location or geographic map. This article proposes a Temporal Attention-based Long Short-Term Memory (TA-LSTM) neural network by combining history, GF information, and location in time series to achieve the optimization heading angle of underwater dead reckoning. Due to its ability to adjust the utilization weights of local and global temporal information in the path, TA-LSTM possesses the capability to continually update neural network model parameters through a data-driven process during the navigation process. This enables the Attention-DR to achieve efficient navigation in regions without prior magnetic maps and overcome navigation failures caused by magnetic field anomalies. The simulation outcomes confirm the efficiency, precision, and practicability of the proposed algorithm. © 2023, CC BY.

关键词： Navigation

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Multi-Branch Mutual-Distillation Transformer for EEG-Based Seizure Subtype Classification

arXiv

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arXiv 2024年

作者： Peng, Ruimin Du, Zhenbang Zhao, Changming Luo, Jingwei Liu, Wenzhong Chen, Xinxing Wu, Dongrui Belt and Road Joint Laboratory on Measurement and Control Technology Huazhong University of Science and Technology Wuhan430074 China AI Platform Software Engineering Research Center Dongfeng Corporation Research & Development Institute Wuhan430072 China China Electronic System Technology Co. Ltd. Beijing100089 China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen518055 China

Cross-subject electroencephalogram (EEG) based seizure subtype classification is very important in precise epilepsy diagnostics. Deep learning is a promising solution, due to its ability to automatically extract latent patterns. However, it usually requires a large amount of training data, which may not always be available in clinical practice. This paper proposes Multi-Branch Mutual-Distillation (MBMD) Transformer for cross-subject EEG-based seizure subtype classification, which can be effectively trained from small labeled data. MBMD Transformer replaces all even-numbered encoder blocks of the vanilla Vision Transformer by our designed multi-branch encoder blocks. A mutual-distillation strategy is proposed to transfer knowledge between the raw EEG data and its wavelets of different frequency bands. Experiments on two public EEG datasets demonstrated that our proposed MBMD Transformer outperformed several traditional machine learning and state-of-the-art deep learning approaches. To our knowledge, this is the first work on knowledge distillation for EEG-based seizure subtype classification. © 2024, CC BY.

关键词： Electroencephalography

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Differential evolution algorithm based on entropy weight method to determine the weight to optimize the configuration of wind, solar, and diesel microgrid 6

Differential evolution algorithm based on entropy weight met...

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2021 6th International Symposium on Advances in Electrical, Electronics and Computer engineering, ISAEECE 2021

作者： Xing, Yongchen Duan, Qing Zhang, Guobao Ma, Chunyan Liu, Wen Long Key Laboratory of Measurement and Control of Complex Systems of Engineering School of Automation Southeast University Nanjing210096 China China Electric Power Research Institute Co. Ltd. Beijing100192 China State Grid Shanghai Energy Interconnection Research Institute Co. Ltd. Shanghai201203 China

In order to enhance the stable operation of the multi-energy complementary microgrid for wind, solar, and diesel storage, reduce operating costs, and solve the problems of large randomness, low accuracy, and slow convergence of traditional microgrid optimization multi-objective decision-making, a differential evolution based on the entropy weight method to determine the weight is proposed. Firstly, we establish a microgrid integrated energy model from the perspectives of system operation stability, economy and environmental protection;combined with the Pareto optimal solution set, multi-objectives are weighted according to the entropy weight method, and the multi-objective optimization problem is transformed into single-objective optimization The problem is to avoid artificial setting of weight factors;the calculation example shows that this method is more economical and reasonable in optimization results, and provides an economic, reliable and environmentally friendly microgrid configuration strategy for users to increase power capacity. © Published under licence by IOP Publishing Ltd.

关键词： Pareto principle

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NewsGPT: ChatGPT Integration for Robot-Reporter

arXiv

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arXiv 2023年

作者： Hireche, Abdelhadi Belkacem, Abdelkader Nasreddine Jamil, Sadia Chen, Chao College of Information Technology United Arab Emirates University Abu Dhabi United Arab Emirates School of International Communications University of Nottingham Ningbo China Academy of Medical Engineering and Translational Medicine Tianjin University Tianjin China Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology Tianjin China

The integration of large language models (LLMs) with social robots has emerged as a promising avenue for enhancing human–robot interactions at a time when news reports generated by artificial intelligence (AI) are gaining in credibility. This integration is expected to intensify and become a more productive resource for journalism, media, communication, and education. In this paper a novel system is proposed that integrates AI’s generative pretrained transformer (GPT) model with the Pepper robot, with the aim of improving the robot’s natural language understanding and response generation capabilities for enhanced social interactions. By leveraging GPT’s powerful language processing capabilities, this system offers a comprehensive pipeline that incorporates voice input recording, speech-to-text transcription, context analysis, and text-to-speech synthesis action generation. The Pepper robot is enabled to comprehend user queries, generate informative responses with general knowledge, maintain contextually relevant conversations, and act as a more domain-oriented news reporter. It is also linked with a news resource and powered with a Google search capability. To evaluate the performance of the framework, experiments were conducted involving a set of diverse questions. The robot’s responses were assessed on the basis of eight criteria, including relevance, context, and fluency. Despite some identified limitations, this system contributes to the field of journalism and human–robot interaction by showcasing the potential of integrating LLMs with social robots. The proposed framework opens up opportunities for improving the conversational capabilities of robots, enabling interactions that are smoother, more engaging, and more context aware. © 2023, CC0.

关键词： Human robot interaction

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Characteristics of gas-solid micro fluidized beds for thermochemical reaction analysis

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Carbon Resources Conversion 2020年第1期3卷 203-218页

作者： Zhennan Han Junrong Yue Xi Zeng Jian Yu Fang Wang Shaozeng Sun Hong Yao Guangqian Luo Xuejing Liu Yining Sun Fu Ding Liangliang Fu Lei Shi Kangjun Wang Jiebin Yang Shaonan Wang Xueqing Chen Dingrong Bai Guangwen Xu Key Laboratory on Resources Chemicals and Material of Ministry of Education Shenyang University of Chemical TechnologyShenyang 110142China The State Key Laboratory of Multi-phase Complex System Institute of Process EngineeringChinese Academy of ScienceBeijing 100190China Combustion Engineering Research Institute School of Energy Science and EngineeringHarbin Institute of TechnologyHarbin 150001China State Key Laboratory of Coal Combustion Huazhong University of Science and TechnologyWuhan 430074China National Institute of Measurement and Technology Chengdu 610021China

Fuel conversion and clean energy reaction systems involve a variety of catalytic and non-catalytic gas-solid thermochemical reactions.A good understanding of the correct reaction mechanism and kinetics,as well as the profiles of reaction products,is of great significance to the development,design,and operation of such reaction *** micro fluidized bed reaction analysis provides an efficient and reliable method to acquire this essential information with low capital and operating costs,low energy consumption and enhanced *** paper provides an overview of the system and its characteristics for the micro fluidized bed reaction analyzer that has been well proven to be a reliable new approach as well as an instrument for characterizing various gas-solid thermochemical reactions.

关键词： Micro fluidized bed Reaction kinetic analysis Isothermal differential reactor Thermochemical reaction characterization

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Detection of Weak Signal Amplitude of Winding Deformation Based on Duffing Oscillator

Detection of Weak Signal Amplitude of Winding Deformation Ba...

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Chinese control Conference (CCC)

作者： Sheng-Min Li Yuan-Yuan He Yue-Yue Che Xu-Xia Sun Academy of Automation & Information Engineering Xi’an University of Technology Xi’an Key Laboratory of Shaanxi Province for Complex System Control and Intelligent Information Processing Xi’an

In order to solve the problem that it is difficult to detect the weak sinusoidal response signal when the frequency response method is used to detect the transformer winding deformation fault online, this paper proposes a method to detect the amplitude of the response signal by using Duffing oscillator. Secondly, in order to solve the influence of the target signal phase shift on the amplitude detection in the actual detection process, a method of first detecting the signal phase using a vibrator array composed of Duffing vibrators and then detecting the amplitude is proposed. Finally, using this method to process the two sets of measured response signals of online detection, the detection results show that the maximum error between the detected signal amplitude and the standard signal is 5. 69%, which meets the requirements of the power industry standard, which proves that the method used in this article is It is feasible in winding deformation detection.

关键词： Phased arrays Simulation Windings Frequency response Power industry Oscillators Standards

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In-Situ Facile Synthesis of Heterostructural Co||Mnco2o4.5/Nc with Active Oxygen Vacancies and its Bifunctional Electrocatalysis for Oxygen Reduction and Oxygen Evolution Reaction

SSRN

引用

SSRN 2022年

作者： Cai, Jiannan Zhang, Xiaofeng Ye, Yanzhu Shi, Yuande Lin, Shen College of Chemistry & Materials Science Fujian Normal University Fuzhou350007 China Fujian Provincial Key Laboratory of Advanced Materials Oriented Chemical Engineering Fuzhou350007 China Fujian Key Laboratory of Polymer Materials Fujian Normal University Fuzhou350007 China Key Laboratory of Measurement and Control System for Coastal Environment Fujian Polytechnic Normal University Fuzhou350300 China

A potential non-noble metal oxide catalyst with its low-cost and efficient catalytic ability attract increasing attention. In this paper, a highly efficient bifunctional electrocatalyst Co-MnCo2O4.5/NC with heterostructure and oxygen vacancies is prepared utilizing solid reaction in-situ . The optimal catalyst is obtained at 650 ℃ with the mass ratio (1:8) of MnCo2O4.5 and Dicyandiamide (DCD). It shows excellent electrocatalytic activity for oxygen reduction reaction (ORR) with high half-wave potential (0.81 V) and limit current density (6.22 mA cm-2 ), which is better than that of the commercial 20% Pt/C(0.81 V, 5.52 mA cm-2 ). At the same time, it also has superior electrocatalytic activity for oxygen evolution reaction (OER) with low overpotential (330 mV) and a faster dynamics process. The superior electrocatalytic properties may resulted from the presence of heterostructure and increasing ratio of oxygen vacancies, which helps to the rapid transfer of electrons and creates more active sites. Moreover, the self-generated N-doped carbon provides high conductivity of the as-prepared Co-MnCo2O4.5/NC composite. It can be seen that the application of interface engineering technologies is useful for improving the performance of the catalyst, providing an effective and facile synthesis strategy for non-noble metal catalyst. © 2022, The Authors. All rights reserved.

关键词： Oxygen vacancies

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Distributed MPC Algorithm for Linear Discrete systems with Communication Noise

Distributed MPC Algorithm for Linear Discrete Systems with C...

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第40届中国控制会议

作者： Duqiao Zhao Ding Liu Linxiong Liu Xia Zhang National & Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Xian University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

In this paper, a distributed MPC algorithm is proposed for linear discrete systems with bounded communication noise and random communication failure. Based on the characteristics of time-varying directed graphs, the convergence of the algorithm is analyzed in the case of communication noise and random communication failure. This algorithm uses the distributed projection dual subgradient algorithm to solve the dual problem and replaces the double stochastic condition of the traditional algorithm with row stochastic condition. The exponential stability of the system is guaranteed. Finally, an example is given to illustrate the performance of the algorithm.

关键词： Distributed MPC Bounded Communication Noise Random Communication Faults Distributed Projection Dual Subgradient Row Stochastic

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Model-Based and Data-Driven control of Event- and Self-Triggered Discrete-Time LTI systems

arXiv

引用

arXiv 2022年

作者： Wang, Xin Berberich, Julian Sun, Jian Wang, Gang Allgöwer, Frank Chen, Jie The Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing10081 China The Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China The University of Stuttgart Institute for Systems Theory and Automatic Control Stuttgart70550 Germany The Department of Control Science and Engineering Tongji University Shanghai201804 China The State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

The present paper considers the model-based and data-driven control of unknown linear time-invariant discretetime systems under event-triggering and self-triggering transmission schemes. To this end, we begin by presenting a dynamic event-triggering scheme (ETS) based on periodic sampling, and a discrete-time looped-functional approach, through which a model-based stability condition is derived. Combining the model-based condition with a recent data-based system representation, a data-driven stability criterion in the form of linear matrix inequalities (LMIs) is established, which also offers a way of co-designing the ETS matrix and the controller. To further alleviate the sampling burden of ETS due to its continuous/periodic detection, a self-triggering scheme (STS) is developed. Leveraging pre-collected input-state data, an algorithm for predicting the next transmission instant is given, while achieving system stability. Finally, numerical simulations showcase the efficacy of ETS and STS in reducing data transmissions as well as of the proposed co-design methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Linear matrix inequalities

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Non-Fourier Heat Conduction based on Self-Adaptive Weight Physics-Informed Neural Networks

Non-Fourier Heat Conduction based on Self-Adaptive Weight Ph...

引用

第40届中国控制会议

作者： Shuyan Shi Ding Liu Zhongdan Zhao National & Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Xi'an University of Technology Shananxi Key Laboratory of Complex System Control and Intelligent Information Processing

This paper establishes the non-Fourier heat conduction model to describe the heat transfer process of mono-crystalline silicon under the condition of unstable thermal field and thermal shock in the Czochralski method.A novel differential equations solver called Physics-Informed Neural Networks（PINN） algorithm was *** with finite element method（FEM）,this method has some advantages like no grid requirement and easily *** order to deal with the unbalance of constraint condition and speed up the convergence,we propose a novel method called Self-Adaptive Weight Physics-Informed Neural Networks（SWPINN）.The comparison of the experimental results of SWPINN and COMSOL verifies the effectiveness of *** modifying the parameter of non-Fourier heat conduction model,this paper obtains the temperature distribution under different heat relaxation ***,comparison between SWPINN and PINN shows that the proposed method has faster convergence speed and higher accuracy.

关键词： Non-Fourier Heat Conduction Physics-Informed Neural Networks Partial Differential Equation Monocrystalline Silicon Czochralski Method

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