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SSRN 2022年

作者： Xiong, Wenxin Liang, Junli Wang, Zhi So, Hing Cheung Department of Computer Science University of Freiburg Freiburg79110 Germany School of Electronics and Information Northwestern Polytechnical University Xi’an710072 China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China Department of Electrical Engineering City University of Hong Kong Hong Kong

Elliptic positioning (EP) has been receiving increasing attention in recent years with the development of multistatic systems. This article considers mitigating the negative effects of biased measurements on the location estimation performance of EP, by introducing a balancing parameter into the traditional non-outlier-resistant least squares type formulation. The resulting problem is then solved by exploiting the augmented Lagrange programming neural network (ALPNN), which is a generally applicable and asymptotically stable nonlinear constrained neurodynamic optimization framework. Moreover, the Cram\'{e}r-Rao lower bound for EP in non-Gaussian noise is derived. The superiority of the proposed ALPNN approach over a number of existing EP estimators is demonstrated through computer simulations. © 2022, The Authors. All rights reserved.

关键词： Parameter estimation

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Distributed Fault-Tolerant Formation Game for Quadrotor UAVs With Hybrid Attacks

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IEEE Transactions on Aerospace and Electronic Systems 2025年

作者： Zhang, Rui-Ming Yao, Xiang-Yu Wang, Leimin Park, Ju H. Ge, Ming-Feng China University of Geosciences School of Mechanical Engineering and Electronic Information Wuhan430074 China Ministry of Education Key Laboratory of System Control and Information Processing Shanghai200240 China China University of Geosciences School of Automation Wuhan430074 China Yeungnam University Department of Electrical Engineering Gyeongsan38541 Korea Republic of

This manuscript studies the distributed faulttolerant formation for quadrotor unmanned aerial vehicles (QUAVs) subject to actuator failures and hybrid cyber attacks via a game-theoretical approach. The desired formation, which aligns with optimal self-interests, is achieved by seeking the Nash equilibrium (NE) of the game under a strongly connected directed graph. First, a secure fault-tolerant NE seeking algorithm is presented to handle actuator failures and false data injection (FDI) attacks, with the false data being measured through extended state observers (ESOs). The proposed algorithm is established on pseudo-gradient dynamics, in which a local estimate law is used to anticipate the actions of other QUAVs. Then, an ESOsbased algorithm is developed to mitigate the influence of FDI and denial-of-service (DoS) attacks, guaranteeing that all QUAVs exponentially converge to an adjustable small domain of NE by Lyapunov stability analysis. This work is distinct from existing studies by addressing the practical scenario, where physical failures and hybrid cyber attacks occur simultaneously in the game framework of QUAVs. Eventually, numerical experiments are conducted to demonstrate the efficacy of theoretical findings. © 1965-2011 IEEE.

关键词： Drones

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Distributing Potential Games on Graphs Part II. Learning with application to platoon matching

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IFAC-PapersOnLine 2020年第2期53卷 6703-6708页

作者： Mohamed I. El-Hawwary Jonas Mårtensson Division of Decision and Control Systems School of Electrical Engineering & Computer Science KTH Royal Institute of Technology SE-100 44 Stockholm Sweden Department of Electrical Power Engineering Faculty of Engineering Cairo University Giza 12613 Egypt

In part I of the paper the problem of distributing potential games over undirected graphs was formulated. A restricted information potential game was designed using state-based formulation. Here, learning Nash equilibria for this game is studied. An algorithm is developed with mainly two phases, an estimation phase and a learning phase. The setting allows for available learning methods of the full information game to be directly incorporated in the learning phase. The result matches the outcome (i.e. converges to the same equilibria) of the full information game. In addition, the design takes into account considerations of convergence time, and synchrony of actions update. The developed distributed game and learning algorithm are used to solve a platoon matching problem for heavy duty vehicles. This serves two objectives. First, it provides a motivation for the presented gaming results. Second, the problem addressed can facilitate platoon matching where it provides a basis for an on-the-go strategy.

关键词： Potential games distributed optimization multi-agents platoon matching

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Nondeterministic Impact of CPU Multithreading on Training Deep Learning Systems

Nondeterministic Impact of CPU Multithreading on Training De...

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International Symposium on Software Reliability engineering (ISSRE)

作者： Guanping Xiao Jun Liu Zheng Zheng Yulei Sui College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics China State Key Laboratory of Novel Software Technology Nanjing University China School of Automation Science and Electrical Engineering. Beihang University China School of Computer Science University of Technology Sydney Australia

ISBN: (纸本)9781665425889

With the wide deployment of deep learning (DL) systems, research in reliable and robust DL is not an option but a priority, especially for safety-critical applications. Unfortunately, DL systems are usually nondeterministic. Due to software-level (e.g., randomness) and hardware-level (e.g., GPUs or CPUs) factors, multiple training runs can generate inconsistent models and yield different evaluation results, even with identical settings and training data on the same implementation framework and hardware platform. Existing studies focus on analyzing software-level nondeterminism factors and the nondeterminism introduced by GPUs. However, the nondeterminism impact of CPU multi-threading on training DL systems has rarely been studied. To fill this knowledge gap, we present the first work of studying the variance and robustness of DL systems impacted by CPU multithreading. Our major contributions are fourfold: 1) An experimental framework based on VirtualBox for analyzing the impact of CPU multithreading on training DL systems; 2) Six findings obtained from our experiments and examination on GitHub DL projects; 3) Five implications to DL researchers and practitioners according to our findings; 4) Released the research data (https://***/DeterministicDeepLearning).

关键词： Training Deep learning Recurrent neural networks Multithreading Training data Hardware Software

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controller synthesis to achieve robust stability against bicoprime factor uncertainty: an LMI approach

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IFAC-PapersOnLine 2020年第2期53卷 7400-7405页

作者： Mihalis Tsiakkas Alexander Lanzon Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Control Systems Centre Department of Electrical and Electronic Engineering School of Engineering University of Manchester Sackville Street Manchester M13 9PL UK

In this paper, a Linear Matrix Inequality approach is presented for synthesizing controllers that robustly stabilize a plant against Bicoprime Factor uncertainty. Following the development of the general case, non-normalized results, the usefulness of normalized Bicoprime Factorizations is studied in this context and shown to be beneficial in deducing the existence of a robustly stabilizing controller for given robust stability margin. Finally, a numerical example is provided to demonstrate the practical applicability of the developed methodology.

关键词： Robust control H-infinity control Coprime factorization Uncertainty Uncertain linear systems Iterative methods

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Energy Efficient Train-Ground mmWave Mobile Relay System for High Speed Railways

arXiv

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arXiv 2022年

作者： Wang, Lei Ai, Bo Niu, Yong Zhong, Zhangdui Mao, Shiwen Wang, Ning Han, Zhu The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing100044 China Peng Cheng Laboratory Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China The National Mobile Communications Research Laboratory Southeast University Nanjing211189 China The Department of Electrical and Computer Engineering Auburn University AuburnAL36949-5201 United States The School of Information Engineering Zhengzhou University Zhengzhou450001 China The Department of Electrical and Computer Engineering The University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of

The rapid development of high-speed railways (HSRs) puts forward high requirements on the corresponding communication system. Millimeter wave (mmWave) can be a promising solution due to its wide bandwidth, narrow beams, and rich spectrum resources. However, with the large number of antenna elements employed, energy-efficient solutions at mmWave frequencies are in great demand. Based on a mmWave HSR communication system with multiple mobile relays (MRs) on top of the train, a dynamic power-control scheme for train-ground communications is proposed. The scheme follows the regular movement characteristics of high-speed trains and considers three phases of train movement: the train enters the cell, all MRs are covered in the cell, and the train leaves the cell. The transmit power is further refined according to the number of MRs in the cell and the distance between the train and the remote radio head. By minimizing energy consumption under the constraints of the transmitted data and transmit power budget, the transmit power is allocated to multiple MRs through the multiplier punitive function-based algorithm. Comprehensive simulation results, where the velocity estimation error is taken into account, are provided to demonstrate the effectiveness of the proposed scheme over several baseline schemes. Copyright © 2022, The Authors. All rights reserved.

关键词： Energy efficiency

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control law and actuator capacity effect on the dynamic performance of a hybrid mass damper;the case of rottweil tower 11

Control law and actuator capacity effect on the dynamic perf...

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11th International Conference on Structural Dynamics, EURODYN 2020

作者： Koutsoloukas, Lefteris Nikitas, Nikolaos Aristidou, Petros Meinhardt, Christian School of Civil Engineering University of Leeds LeedsLS2 9JT United Kingdom School of Civil Engineering University of Leeds LeedsLS2 9JT United Kingdom Department of Electrical Engineering & Computer Engineering and Informatics Cyprus University of Technology Limassol Limassol3036 Cyprus GERB Vibration Control Systems Roedernallee 174-176 Berlin13407 Germany

ISBN: (纸本)9786188507203

This paper considers different vibration control options for a real high-rise tower subjected to real wind loading. To mitigate excessive responses, the tower utilizes a hybrid passive - active control system with a relatively small actuator capacity. Firstly, the methodology for establishing a reduced order numerical model of the tower from a finite element realization is presented. Subsequently, to deal with physical constraints, a Model Predictive control (MPC) algorithm is employed and compared to a more conventional Linear Quadratic Regulator (LQR). In both cases, the algorithms managed to keep the dynamic displacements within the set desired limit. It was concluded that, the MPC had a better performance when compared to the LQR in terms of peak amplitudes at the expense though of energy. © 2020 European Association for Structural Dynamics. All rights reserved.

关键词： Model predictive control

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Distributing Potential Games on Graphs Part I. Game formulation

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IFAC-PapersOnLine 2020年第2期53卷 6697-6702页

The paper presents the problem of distributing potential games over communication graphs. Suppose a potential game can be designed for a group of agents (players) where each has access to all others’ actions (strategies). The paper shows how to design a corresponding potential game for these agents if the full information assumption is replaced with communication over a network depicted by undirected graphs with certain properties. A state-based formulation for potential games is utilized. This provides degrees of freedom to handle the previous information limitation. Notions of Nash’s equilibria for the developed game (called here distributed potential game) are presented, and relations between these equilibria and those of the full information game are studied. In part II of the paper learning Nash equilibria for the newly developed game is studied. The development focuses on providing a way to utilize available algorithms of the full information game. The motivation for the results comes from a platoon matching problem for heavy duty vehicles. Utilizing the newly developed distributed game, recent results based on potential games can be extended, providing a basis for an on-the-go strategy where platoon matching on road networks can be solved locally.

关键词： Potential games distributed optimization multi-agents

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Signal Frequency Estimation Based on RNN

Signal Frequency Estimation Based on RNN

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Chinese control and Decision Conference, CCDC

作者： Bin Huang Chun-Liang Lin Weihai Chen Chia-Feng Juang Xingming Wu School of Automation Science and Electrical Engineering Beihang University Beijing China College of Electrical Engineering and Computer Science National Chung Hsing University Taichung Taiwan

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

Signal frequency estimation is a fundamental issue in the domain of signal processing. In this paper, we proposed a novel framework, named FreqEnet (Frequency estimation network), for estimating frequency based on deep learning method. The signal frequency estimation refers to as a regression issue and predict it with LTSM module. The framework is exceedingly concise, consisted of only three LSTM and one fully connect layers, and the running time is less than 0.3 ms on CPU (i7-7700, 3.60 GHz). Two periodic signals are generated for training our model. In addition, uniform and Gauss white noise are introduce to original signal for evaluating the robustness and generalization of the framework. In addition, the proposed method performs extremely excellence in processing latent. Even if given only one periodic piece of signal, the method could predicts a precise result. Extensive experiments demonstrate that FreqEnet achieves competitive performance of estimating frequency.

关键词： Frequency estimation Training Machine learning White noise Neural networks Signal to noise ratio

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Modeling of Main Steam Temperature Using an Improved Fuzzy Genetic Algorithm

Modeling of Main Steam Temperature Using an Improved Fuzzy G...

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第三十九届中国控制会议

作者： Chuanliang Cheng Chen Peng De-liang Zeng Tengfei Zhang School of Mechatronic Engineering and Automation Shanghai University School of Control and Computer Engineering North China Electric Power University College of Automation and College of Artificial Intelligence Nanjing University of Posts and Telecommunications

Main steam temperature is an important parameter in thermal power plants. In order to get a better control effect, an improved fuzzy genetic algorithm（FGA） modelling method is proposed in this paper. Different from traditional identification methods, the improved FGA is more suitable for modeling the dynamic process of the main steam temperature which has the characteristics of strong coupling and nonlinearity. Firstly, to solve the nonlinear problem, a fuzzy thought is introduced to partition the whole operating region into several local regions. Then an improved genetic algorithm（GA） which has better identification capability is proposed to build the linear model in each local region. The nonlinear dynamic process of studied system is elaborately approximated by the fuzzy combination of the local linear models. The simulation results show that the improved FGA can achieve satisfactory effects even in the case of strong coupling and nonlinearity, which provides theory foundation for other control methods.

关键词： Main steam temperature Fuzzy genetic algorithm Scheduling program Local linear models

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