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General electronic structure calculation method for twisted systems

Physical Review B 2025年第7期111卷 075434-075434页

作者： Junxi Yu Shifeng Qian Cheng-Cheng Liu Centre for Quantum Physics Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement (MOE) and Beijing Key Lab of Nanophotonics and Ultrafine Optoelectronic Systems School of Physics Beijing Institute of Technology Beijing 100081 China Anhui Province Key Laboratory for Control and Applications of Optoelectronic Information Materials Department of Physics Anhui Normal University Anhui Wuhu 241000 China

In recent years, two-dimensional twisted systems have gained increasing attention. However, calculating the electronic structures in twisted materials has remained a challenge. To address this, we have developed a general computational methodology that can generate twisted geometries starting from a monolayer structure and obtain a precisely relaxed twisted structure through a machine learning-based method. Then, the electronic structure properties of the twisted material are calculated using the tight-binding (TB) and continuum model methods; thus, the entire process requires minimal computational resources. We introduce the theoretical methods for generating twisted structures and computing their electronic properties, and further provide calculations and brief analyses of the electronic structure properties for several typical two-dimensional materials with different characteristics. This paper serves as a solid foundation for researchers interested in studying twisted systems.

关键词： Electronic properties

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Contextual Multi-Armed Bandit-Based Dynamic Cooperative Link Configuration for AUV in UWASNs With Energy Harvesting

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IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Dai, Jun Li, Xinbin Han, Song Yu, Junzhi Liu, Zhixin Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao066004 China Yanshan University Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province Qinhuangdao066004 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics BIC-ESAT College of Engineering Beijing100871 China

This paper investigates the cooperative link configuration problem for Autonomous Underwater Vehicle (AUV) in Underwater Acoustic (UWA) sensor networks with Energy Harvesting (EH), which aims to maximize long-term cumulative capacity by jointly optimizing cooperation relay, AUV transmission power, and relay transmission power. Subject to unknown time-varying Channel State Information (CSI), unpredictable stochastic EH, and variable communication topology caused by AUV mobility, the proposed problem is an unknown dynamic combination decision optimization problem. To resist the change of the dynamic UWA communication topology with unknown time-varying CSI and EH, a novel collaborative contextual multi-armed bandit learning framework is proposed, which allows relay nodes to learn cooperatively and enriches the learning information of relays. Consequently, the proposed learning framework can resist the change of the dynamic UWA communication topology efficiently, thereby achieving the superior link configuration quickly. Besides, a learning-rate adjustment rule for the dynamic UWA communication topology is proposed to adaptively balance the exploration-exploitation, thereby avoiding missing the real superior joint relay-power configuration. Finally, simulation results show the significantly superiority of the proposed scheme. © 2015 IEEE.

关键词： Cooperative communication

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Energy management in smart homes with adversary detection and noise mitigation using a moving prediction window scheme

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Sustainable Energy, Grids and Networks 2025年 43卷

作者： Hamid Reza Babaei Ghazvini Saeed Adelipour Mohammad Haeri Advanced Control Systems Lab. Electrical Engineering Department Sharif University of Technology Tehran 11155-4363 Iran

This paper presents an energy management algorithm for scheduling a large number of residential households, utilizing the moving prediction window to make it resilient against false data injection attacks and communication noise. We model multiple communities of smart homes, each managed by a local controller, where self-interested residential households engage in a global non-cooperative game. The cost functions of the households are influenced by a constrained aggregated power consumption term across all households from all communities. The interactions among households are modeled through a multi-community aggregative game. To reach a Nash equilibrium, we propose an iterative algorithm wherein local controllers estimate the coupling aggregate term and corresponding Lagrange multiplier for their respective households and collaborate with other controllers via an unreliable communication network to refine the aggregate estimations. Given the vulnerability of the communication network to external intrusions and the potential for internal controllers to behave maliciously, we explore a moving horizon window technique to detect false data injection attacks and mitigate communication noise. In this regard, first, a moving horizon estimator predicts the community’s current behavior based on historical data; second, a residual-based detection mechanism flags an attack when predicted residuals exceed a dynamic threshold; and third, corrupted measurements are discarded, and the average of the predictions is used in the Krasnoselskii-Mann update to reduce the noise impact. Numerical simulations show the effectiveness of the proposed algorithm in increasing the speed of reaching consensus by about 30 percent while managing the energy consumption of households.

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Freeway and Side Road Balancing control Scheme Using MFAILC Approach 6

Freeway and Side Road Balancing Control Scheme Using MFAILC ...

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2017 IEEE 6th Data Driven control and Learning systems Conference (DDCLS’17)

作者： Jing Mei Ye Ren Shangtai Jin Zhongsheng Hou Advanced Control Systems Lab Beijing Jiaotong University

ISBN: (纸本)9781509054626

In order to alleviate the congestion between the side road and the freeway, a novel balancing control scheme is proposed based on model free adaptive iterative learning control(MFAILC) in this paper. controller realization possesses the model free attribute to merely utilize the measured input and output(I/O) data of the controlled plant of side road and freeway. The control performance is enhanced by utilizing the repetitive information collected from the controlled system. In the last section, the proposed MFAILC based balancing control method is to show the effectiveness.

关键词： Balancing control Macroscopic Traffic Flow Model Model Free Adaptive Iterative Learning control(MFAILC) Store and Forward Model(SF Model)

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Quasi-Newton method based control design for unknown nonlinear systems with input constraints

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Science China(Information Sciences) 2020年第5期63卷 224-226页

作者： Shuangshuang XIONG Zhongsheng HOU Chenkun YIN Advanced Control Systems Lab School of Electronic and Information EngineeringBeijing Jiaotong University School of Automation Qingdao University

Dear editor,With the development in digital computers, various and huge data of controlled plants are obtained and stored, which has led to a rapid growth in the application of numerical methods in controller design. In recent years, the quasi-Newton method [1, 2], as one of the powerful numerical methods which has superlinear convergence speed

关键词： Newton Quasi-Newton method based control design for unknown nonlinear systems with input constraints

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Generalized projective synchronization of chaotic satellites problem using linear matrix inequality

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International Journal of Dynamics and control 2014年第4期2卷 577-586页

作者： Farid, Yousef Moghaddam, Tahmine Vedadi Advanced Power and Control Systems Lab. EE Department Imam Khomeini International University Qazvin Iran

In this paper, a systematic design procedure for generalized projective synchronization between two identical chaotic satellites systems based on feedback control theory is proposed. This method is developed based on suitable feedback control, combined with the Lyapunov stability theory and linear matrix inequality formulation as a solution of the optimal problem. Two necessary and sufficient conditions for the asymptotic stability of the error dynamic system are obtained. Compared with the predictive-based control method, the proposed method shows comparable and superior performance. The effectiveness of the obtained results is illustrated by numerical simulations. © 2014, Springer-Verlag Berlin Heidelberg.

关键词： Linear matrix inequalities

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Model-free Adaptive control for a Vapour-Compression Refrigeration Benchmark Process

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IFAC-PapersOnLine 2018年第4期51卷 527-532页

作者： Yu, Xian Hou, Zhongsheng Zhang, Xin Advanced Control Systems Lab School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China

A model-free adaptive control (MFAC) is applied to the Refrigeration systems based on Vapour Compression of the BENCHMARK PID 2018. A SISO MFAC controller and a MIMO MFAC controller are designed to control the outlet temperature of evaporator secondary flux and the superheating degree of refrigerant at evaporator outlet by manipulating the expansion valve opening and the compressor speed. The two designed controllers are the pure data driven control methods without using any model information of the refrigeration process in the control implementation by virtue of the dynamic linearization technique, and the PID controllers can be considered as special cases of the two designed controllers. The qualitative and quantitative comparison results between the MFAC schemes and the default PID controllers given in the simulation platform provided by the Benchmark PID 2018 demonstrate the effectiveness of the two designed controllers. © 2018

关键词： Process control Adaptive control systems controllers Electric control equipment Evaporators Linearization Proportional control systems Refrigeration Three term control systems control implementation Dynamic linearization Model free adaptive control Quantitative comparison Refrigeration system Vapour compression refrigeration systems Vapour compression refrigerations Vapour compressions

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Neural Network State Learning Based Adaptive Terminal ILC for Tracking Iteration-varying Target Points

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International Journal of Automation and computing 2015年第3期12卷 266-272页

作者： Yu Liu Rong-Hu Chi Zhong-Sheng Hou School of Automation and Electronic Engineering Qingdao University of Science and Technology Advanced Control Systems Lab School of Electronics and Information Engineering Beijing Jiaotong University

Terminal iterative learning control(TILC) is developed to reduce the error between system output and a fixed desired point at the terminal end of operation interval over iterations under strictly identical initial conditions. In this work, the initial states are not required to be identical further but can be varying from iteration to iteration. In addition, the desired terminal point is not fixed any more but is allowed to change run-to-run. Consequently, a new adaptive TILC is proposed with a neural network initial state learning mechanism to achieve the learning objective over iterations. The neural network is used to approximate the effect of iteration-varying initial states on the terminal output and the neural network weights are identified iteratively along the iteration axis.A dead-zone scheme is developed such that both learning and adaptation are performed only if the terminal tracking error is outside a designated error bound. It is shown that the proposed approach is able to track run-varying terminal desired points fast with a specified tracking accuracy beyond the initial state variance.

关键词： Adaptive terminal iterative learning control neural network initial state learning iteration-varying terminal desired points ini

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Experimental comparison among three typical data-driven control algorithms

Experimental comparison among three typical data-driven cont...

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15th International Symposium on Artificial Life and Robotics, AROB '10

作者： Jin, Shangtai Li, Yongqiang Zhu, Yuanming Hao, Jiangen Hou, Zhongsheng Advanced Control Systems Lab. Beijing Jiaotong University Beijing China

ISBN: (纸本)9784990288044

The differences, similarities and insights of three typical data-driven control algorithms, model free adaptive control (MFAC), iterative feedback tuning (IFT) and virtual reference feedback tuning (VRFT), are briefly discussed, and these differences, similarities and insights are certified through a series of experiments on the three-tank water system in our university lab. © 2010 ISAROB.

关键词： Iterative methods

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The iterative learning approach for vehicle queuing length balanced-control of the signalized isolated intersection

The iterative learning approach for vehicle queuing length b...

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作者： Hao, Jiangen Hou, Zhongsheng Bu, Xuhui Advanced Control Systems Lab Beijing Jiaotong University Beijing 100044 China

ISBN: (纸本)9789881725592

In this work, the iterative learning control approach is proposed to address the signalized isolated intersection control problem. The signal timing should be adjusted according to the real-time daily-repeated traffic demand to ensure the full utilization of green time. However, it is difficult to establish the exact mathematic model of isolated intersection with the time-varying demand. The iterative learning control approach requires much less system modeling knowledge and also rejects the exogenous traffic perturbations. Rigorous analyses show that the proposed learning control scheme can guarantee the convergence of the vehicle queuing length difference to the desired one. The effectiveness of the proposed approach is also verified through simulations. © 2011 Chinese Assoc of Automati.

关键词： Learning algorithms

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