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Fixed-Time H∞ Control for Port-Controlled Hamiltonian Systems

IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2019年第7期64卷 2753-2765页

作者： Liu, Xinggui Liao, Xiaofeng Southwest Univ Coll Elect & Informat Engn Chongqing 400715 Peoples R China Yunnan Agr Univ Dept Appl Math Kunming 650201 Yunnan Peoples R China Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China Chongqing Univ Coll Comp Sci Chongqing 400715 Peoples R China Southwest Univ Coll Elect & Infor Mat Engn Chongqing 400715 Peoples R China

In this paper, the locally fixed-time and globally fixed-time H-infinity control problems for the port-controlled Hamiltonian (PCH) systems are investigated via the interconnection and damping assignment passivity-based control (IDA-PBC) technique. Compared with finite-time stabilization, where the convergence time of the closed-loop system's states relies on the initial values, the settling time of fixed-time stabilization can be adjusted to achieve desired equilibrium point regardless of initial conditions. The concepts of fixed-time H-infinity control, fixed-time stability region (or region of attraction), and fixed-time stability boundary are presented in this paper, and the criterions of globally fixed-time attractivity of a prespecified locally fixed-time stability region are obtained. Combining the locally fixed-time stability of an equilibrium point and the globally fixed-time attractivity of a prespecified fixed-time stability region, the globally fixed-time H-infinity control problem of PCH system is effectively solved. Two novel control laws are designed to deal with the globally fixed-time H(infinity )control problem, and the conservativeness in estimating the settling time is also briefly discussed. An illustrative example shows that the theoretical results obtained in this paper work very well in the fixed-time H-infinity control design for PCH systems.

关键词： Fixed-time H(infinity )control fixed-time attractivity fixed-time stability region port-Hamiltonian (PH) systems

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Off-Line Evaluation of Indoor Positioning Systems in Different Scenarios: The Experiences From IPIN 2020 Competition

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IEEE SENSORS JOURNAL 2022年第6期22卷 5011-5054页

作者： Potorti, Francesco Torres-Sospedra, Joaquin Quezada-Gaibor, Darwin Jimenez, Antonio Ramon Seco, Fernando Perez-Navarro, Antoni Ortiz, Miguel Zhu, Ni Renaudin, Valerie Ichikari, Ryosuke Shimomura, Ryo Ohta, Nozomu Nagae, Satsuki Kurata, Takeshi Wei, Dongyan Ji, Xinchun Zhang, Wenchao Kram, Sebastian Stahlke, Maximilian Mutschler, Christopher Crivello, Antonino Barsocchi, Paolo Girolami, Michele Palumbo, Filippo Chen, Ruizhi Wu, Yuan Li, Wei Yu, Yue Xu, Shihao Huang, Lixiong Liu, Tao Kuang, Jian Niu, Xiaoji Yoshida, Takuto Nagata, Yoshiteru Fukushima, Yuto Fukatani, Nobuya Hayashida, Nozomi Asai, Yusuke Urano, Kenta Ge, Wenfei Lee, Nien-Ting Fang, Shih-Hau Jie, You-Cheng Young, Shawn-Rong Chien, Ying-Ren Yu, Chih-Chieh Ma, Chengqi Wu, Bang Zhang, Wei Wang, Yankun Fan, Yonglei Poslad, Stefan Selviah, David R. Wang, Weixi Yuan, Hong Yonamoto, Yoshitomo Yamaguchi, Masahiro Kaichi, Tomoya Zhou, Baoding Liu, Xu Gu, Zhining Yang, Chengjing Wu, Zhiqian Xie, Doudou Huang, Can Zheng, Lingxiang Peng, Ao Jin, Ge Wang, Qu Luo, Haiyong Xiong, Hao Bao, Linfeng Zhang, Pushuo Zhao, Fang Yu, Chia-An Hung, Chun-Hao Antsfeld, Leonid Chidlovskii, Boris Jiang, Haitao Xia, Ming Yan, Dayu Li, Yuhang Dong, Yitong Silva, Ivo Pendao, Cristiano Meneses, Filipe Nicolau, Maria Joao Costa, Antonio Moreira, Adriano De Cock, Cedric Plets, David Opiela, Miroslav Dzama, Jakub Zhang, Liqiang Li, Hu Chen, Boxuan Liu, Yu Yean, Seanglidet Lim, Bo Zhi Teo, Wei Jie Lee, Bu Sung Oh, Hong Lye CNR Informat Sci & Technol Inst I-56124 Pisa Italy UBIK Geospatial Solut SL Castellon de La Plana 12006 Spain Univ Jaume 1 Inst New Imaging Technol Castellon de La Plana 12006 Spain Tampere Univ Elect Engn Unit Tampere 33100 Finland Ctr Automat & Robot CSIC UPM Arganda Del Rey 28500 Spain Univ Oberta Catalunya Fac Comp Sci Multimedia & Telecommun Barcelona 08860 Spain Univ Oberta Catalunya Internet Interdisciplinary Inst IN3 Barcelona 08860 Spain Univ Gustave Eiffel IFSTTAR AME GEOLOC F-44344 Bouguenais France Natl Inst Adv Ind Sci & Technol Tsukuba Ibaraki 3058560 Japan Univ Tsukuba Dept Intelligent Interact Technol Tsukuba Ibaraki 3058573 Japan Univ Tsukuba Fac Engn Informat & Syst Tsukuba Ibaraki 3058573 Japan Chinese Acad Sci Aerosp Informat Res Inst Beijing 100094 Peoples R China Fraunhofer Inst Integrated Circuits IIS D-90411 Nurnberg Germany Wuhan Univ State Key Lab Informat Engn Surveying Mapping & R Wuhan 430072 Peoples R China Wuhan Univ GNSS Res Ctr Wuhan 430072 Peoples R China Wuhan Univ Collaborat Innovat Ctr Geospatial Technol Wuhan 430072 Peoples R China Nagoya Univ Grad Sch Engn Dept Informat & Commun Engn Nagoya Aichi 4648601 Japan Yuan Ze Univ Dept Elect Engn Taoyuan 32003 Taiwan MOST Joint Res Ctr AI Technol & All Vista Healthc Taipei 10617 Taiwan Natl Ilan Univ Dept Elect Engn Yilan 26047 Taiwan UCL Elect & Elect Engn Dept London WC1E 7JE England Queen Mary Univ London Elect Engn & Comp Sci Dept London E1 4NS England Shenzhen Univ Dept Res Inst Smart Cities Shenzhen 518060 Peoples R China Keio Univ Fac Sci & Technol Yokohama Kanagawa 2238522 Japan Nippon Elect Co Ltd NEC Kawasaki Kanagawa 2118666 Japan Shenzhen Univ Coll Civil & Transportat Engn Shenzhen 518060 Peoples R China Shenzhen Univ Sch Architecture & Urban Planning Shenzhen 518060 Peoples R China Xiamen Univ Dept Informat & Commun Engn Xiamen 361005 Peoples R China Beijing Univ Posts & Telecommun Sch Artificial Intelligence Beijing 100876 Peoples

Every year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoor positioning and navigation purposes. Through fair comparison of the performance achieved by each system, the competition was able to identify the most promising approaches and to pinpoint the most critical working conditions. In 2020, the competition included 5 diverse off-site off-site Tracks, each resembling real use cases and challenges for indoor positioning. The results in terms of participation and accuracy of the proposed systems have been encouraging. The best performing competitors obtained a third quartile of error of 1 m for the Smartphone Track and 0.5 m for the Foot-mounted IMU Track. While not running on physical systems, but only as algorithms, these results represent impressive achievements.

关键词： Sensor phenomena and characterization Indoor navigation Testing Standards Satellite broadcasting Recurrent neural networks Received signal strength indicator Indoor positioning and navigation evaluation smartphone-based positioning foot-mounted IMU positioning in industrial scenarios and factories vehicle-positioning

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Recurrent neural network for combined economic and emission dispatch

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APPLIED INTELLIGENCE 2018年第8期48卷 2180-2198页

作者： Deng, Ting He, Xing Zeng, Zhigang Southwest Univ Chongqing Key Lab Nonlinear Circuits & Intelligen Coll Elect & Informat Engn Chongqing 400715 Peoples R China Huazhong Univ Sci & Technol Sch Automat Wuhan 430074 Peoples R China

Recently, the combined economic and emission dispatch (CEED) problem, which aims to simultaneously decrease fuel cost and reduce environmental emissions of power systems, has been a widespread concern. To improve the utilization efficiency of primary energy, combined heat and power (CHP) units are likely to play an important role in the future. The goal of this study is to propose an approach to solve the CEED problems in a CHP system which consists of eight power generators (PGs), two CHP units and one heat only unit. Owing to the existence of power loss in power transmission line and the non-convex feasible region of CHP units, the proposed problem is a nonlinear, multi-constraints, non-convex multi-objectives (MO) optimization problem. To deal with it, a recurrent neural network (RNN) combined with a novel technique is developed. It means that the feasible region is separated into two convex regions by using two binary variables to search for different regions. In the frame of the neurodynamic optimization, existence and convergence of the dynamic model are analyzed. It shows that the convergence solution obtained by RNN is the optimal solution of CEED problem. Numerical simulation results show that the proposed algorithm can generate solutions efficiently.

关键词： Combined heat and power units Combined economic and emission dispatch Recurrent neural network

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Autonomic Nervous Pattern of Motion Interference in Real-Time Anxiety Detection

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IEEE ACCESS 2018年 6卷 69763-69768页

作者： Liu, Hong Wen, Wanhui Zhang, Jie Liu, Guangyuan Yang, Zhaofang Southwest Univ Sch Elect & Informat Engn Chongqing 400715 Peoples R China Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China Southwest Univ Coll Comp & Informat Sci Chongqing 400715 Peoples R China

Anxiety is a kind of extremely negative emotion, and long-term anxiety is the cause of many serious physical and mental diseases. In daily life, real-time and accurate detection of anxiety state is conducive to block the physical and mental hazards of anxiety timely. Anxiety detection based on autonomic nervous patterns has achieved high-detection precision in certain scenes. However, motion interferes with anxiety detection in arbitrary scenes of daily life, leading to the false report of anxiety. This paper designed four different intensities of motions to analyze the autonomic nervous activity of typical motion states, found out the motion states with similar autonomic nervous patterns to the anxiety status, and identified the motion interference that would cause false detection of anxiety state. A multi-modal real-time anxiety detection system was built in this paper. The ability of the above system to detect motion interference and exclude false anxiety status was validated both in the laboratory and in real life scenarios.

关键词： Anxiety detection motion interference autonomic nervous mechanism electrocardiogram triple-axis acceleration

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Convergence Analysis of a Fixed Point Algorithm Under Maximum Complex Correntropy Criterion

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IEEE SIGNAL PROCESSING LETTERS 2018年第12期25卷 1830-1834页

作者： Qian, Guobing Wang, Shiyuan Wang, Lidan Duan, Shukai Southwest Univ Chongqing Key Lab Nonlinear Circuits & Intelligen Coll Elect & Informat Engn Chongqing 400715 Peoples R China Southwest Univ Sch Math & Stat Chongqing 400715 Peoples R China

With the emergence of complex correntropy, the maximum complex correntropy criterion (MCCC) has been applied to the complex-domain adaptive filtering. The MCCC uses the fixed point method to find the optimal solution, which provides good robustness in the non-Gaussian noise environment, especially for the impulse noise. However, the convergence analysis for the fixed point method is limited to the real-domain filtering. In this letter, we provide the convergence analysis of fixed point based MCCC algorithm in complex-domain filtering. First, by using the matrix inversion lemma, we rewrite the MCCC algorithm to a gradient-like version. In addition, we provide two computationally efficient versions of MCCC. Then, we provide the stability analysis and obtain the excess mean square error for MCCC. Finally, simulation results confirm the correctness of the convergence analysis in this letter.

关键词： Complex correntropy fixed point stability analysis EMSE

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A novel fixed-point algorithm for constrained independent component analysis

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EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING 2019年第1期2019卷 1页

作者： Qian, Guobing Wang, Lidan Wang, Shiyuan Duan, Shukai Southwest Univ Chongqing Key Lab Nonlinear Circuits & Intelligen Coll Elect & Informat Engn Chongqing 400715 Peoples R China Southwest Univ Sch Math & Stat Chongqing 400715 Peoples R China

Constrained independent component analysis (ICA) is an effective method for solving the blind source separation with a prior knowledge. However, most constrained ICA algorithms are proposed for the real-valued sources. In this paper, a novel constrained noncircular complex fast independent component analysis (c-ncFastICA) algorithm based on the fixed-point learning is proposed to address the complex-valued sources. The c-ncFastICA algorithm uses the augmented Lagrangian method to obtain a new cost function and then utilizes the quasi-Newton method to search its optimal solution. Compared with other ICA and constrained ICA algorithms, c-ncFastICA has better separation performance. Simulations confirm the effectiveness and superiority of the c-ncFastICA algorithm.

关键词： Constrained ICA Noncircular Complex Fixed-point

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A quick-response framework for multi-user computation offloading in mobile cloud computing

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2018年 81卷 166-176页

作者： Kuang, Zhikai Guo, Songtao Liu, Jiadi Yang, Yuanyuan Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China SUNY Stony Brook Dept Elect & Comp Engn Stony Brook NY 11794 USA

The execution of much sophisticated applications on the resource-constrained mobile device will lead to the fast exhaustion of the battery of mobile device. Therefore, mobile cloud computing (MCC) is regarded as an energy-effective approach by offloading tasks from mobile device to the resource-enough cloud, which cannot only save energy for mobile devices but also prolong the operation time of battery. However, it still remains a challenging issue to coordinate task offloading among mobile devices and get offloading results quickly at the same time. In this paper, we propose an agent-based MCC framework to enable the device to receive offloading results faster by making offloading decision on the agent. Moreover, to get an offloading strategy, we formulate the problem of maximizing energy savings among multiple users under the completion time and bandwidth constraints. To solve the optimization problem, we propose a Dynamic Programming After Filtering (DPAF) algorithm. In the algorithm, firstly, the original offloading problem is transformed to the classic 0-1 Knapsack problem by the filtering process on the agent. Furthermore, we adopt dynamic programming algorithm to find an optimal offloading strategy. Simulation results show that the framework can more quickly get response from agent than other schemes and the DPAF algorithm outperforms other solutions in energy saving. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Computation offloading Energy saving Task filtering Completion time constraint Mobile cloud computing

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Tomogravity space based traffic matrix estimation in data center networks

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2018年 86卷 39-50页

作者： Liu, Guiyan Guo, Songtao Zhao, Quanjun Yang, Yuanyuan Southwest Univ Chongqing Key Lab Nonlinear Circuits & Intelligen Coll Elect & Informat Engn Chongqing 400715 Peoples R China SUNY Stony Brook Dept Elect & Comp Engn Stony Brook NY 11794 USA

Traffic matrix (TM) is an important input requirement to better system management in data center networks (DCNs). Directly estimating TM is cost and difficult since the flow behaviors in DCNs are irregular and the TM across the Top of Rack (ToR) switches is huge. Although indirect TM estimation tomography based methods can be applied in DCNs after decomposing tree-like structure, these approaches require a good prior TM obtained by gravity model to improve estimation accuracy. In addition, data collection from the Simple Network Management Protocol (SNMP) employed in DCNs can result in unavoidable data missing and data errors. Therefore, it is necessary to estimate a good prior TM and study the effect of link data missing or data errors on estimation accuracy. In this paper, we utilize the tomogravity space to achieve TM estimation in decomposed tree-like DCNs without requiring a good prior TM because the gravity model can be replaced by gravity space. We propose two iterative algorithms to estimate TM between tomogravity space and gravity space, and use similar-Mahalanobis distance as a metric to control estimation errors. One iterative algorithm utilizes a prior TM calculated based on coarse-grained traffic characteristics, whereas the other considers moderate link data missing and no prior TM based on traffic characteristics. To further separately discuss the effect of link data errors, we obtain desirable link measurement from packet trace and routing matrix. Numerical results demonstrate that our iterative algorithms outperform the existing algorithms in terms of controlling data errors based on decomposed structure and produce robust results when adding different noise level on the link data. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Data center networks Traffic matrix estimation Coarse-grained traffic characteristics Iterative algorithms Tomogravity space

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Fully state constraint impulsive control for non-autonomous delayed nonlinear dynamic systems

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nonlinear ANALYSIS-HYBRID SYSTEMS 2018年 29卷 383-394页

作者： Li, Liangliang Li, Chuandong Li, Hongfei Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China Chongqing Three Gorges Univ Sch Math & Stat Chongqing 404100 Peoples R China

This paper investigates the problem of exponential stabilization criterion for nonautonomous delayed dynamic systems via state constraint impulsive control. It is fundamentally different from the traditional impulsive feedback control, and it has a good adaptation to different actual situations. Combining with convex analysis, inductive method and matrix measure theory, some sufficient conditions are obtained to ensure exponential stabilization for delayed system by using the linear feedback constraint impulsive controllers. Meanwhile, several examples with simulations are given to validate the effectiveness of the proposed criteria. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Fully state constraints Convex analysis Impulsive control Delayed nonlinear dynamic systems

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Secrecy Performance Analysis of SIMO Systems Over Correlated κ-μ Shadowed Fading Channels

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IEEE ACCESS 2019年 7卷 86090-86101页

作者： Sun, Jiangfeng Bie, Hongxia Li, Xingwang Zhang, Jiayi Pan, Gaofeng Rabie, Khaled M. Beijing Univ Posts & Telecommun Sch Informat & Commun Engn Beijing 100876 Peoples R China Henan Polytech Univ Sch Phys & Elect Informat Engn Jiaozuo 454000 Peoples R China Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing 100044 Peoples R China Southwest Univ Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China Univ Lancaster Sch Comp & Commun Lancaster LA1 4YW England Manchester Metropolitan Univ Sch Elect Engn Manchester M15 6BH Lancs England

In this paper, the secrecy performance of single-input-multiple-output systems over correlated kappa-mu shadowed fading channels is investigated. In particular, based on the classic Wyner's wiretap model, we derive analytical expressions for secure outage probability (SOP) and the probability of strictly positive secrecy capacity (SPSC) over correlated kappa-mu shadowed fading channels. In order to further study the impact of channel parameters on the secrecy performance, novel SOP and the probability of SPSC over independent and identically distributed kappa-mu shadowed fading channels are also obtained. In addition, we discuss the asymptotic expressions of the SOP and the SPSC. The match between the analytical results and simulations is excellent for all parameters under considerations. It is interesting to find that the results show that when the signal-to-noise ratio of the main channel is lower than that of the eavesdropping channel, the larger value of correlation coefficient is helpful to improve the secrecy performance and vice versa.

关键词： Single-input multiple-output kappa-mu shadowed fading the probability of strictly positive secrecy capacity (SPSC) secure outage probability (SOP)

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