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Event-triggered Kalman-consensus filter for two-target tracking sensor networks

ISA TRANSACTIONS 2017年第Part1期71卷 103-111页

作者： Su, Housheng Li, Zhenghao Ye, Yanyan Huazhong Univ Sci & Technol Educ Minist China Image Proc & Intelligent Control Key Lab Sch Automat Luoyu Rd 1037 Wuhan 430074 Hubei Peoples R China

This paper is concerned with the problem of event-triggered Kalman-consensus filter for two-target tracking sensor networks. According to the event-triggered protocol and the mean-square analysis, a suboptimal Kalman gain matrix is derived and a suboptimal event-triggered distributed filter is obtained. Based on the Kalman-consensus filter protocol, all sensors which only depend on its neighbors' information can track their corresponding targets. Furthermore, utilizing Lyapunov method and matrix theory, some sufficient conditions are presented for ensuring the stability of the system. Finally, a simulation example is presented to verify the effectiveness of the proposed event triggered protocol. (C) 2017 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： Event-triggered Kalman-consensus filter Suboptimal Two-target Sensor network

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Lagrange Stability for T-S Fuzzy Memristive Neural Networks with Time-Varying Delays on Time Scales

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IEEE TRANSACTIONS ON FUZZY SYSTEMS 2018年第3期26卷 1091-1103页

作者： Xiao, Qiang Zeng, Zhigang Huazhong Univ Sci & Technol HUST Ind Technol Res Inst Guangdong Prov Key Lab Digital Mfg EquipmentSch Key Lab Image Proc & Intelligent ControlEduc Min Wuhan 430074 Hubei Peoples R China

The existed results of Lagrange stability for neural networks (NNs) are scale-free, and hence, conservativeness appears naturally. A class of Takagi-Sugeno (T-S) fuzzy memristive NNs (FMNNs) with time-varying delays is considered on time scales. First, a class of FMNNs is formulated using characteristics of memristors and T-S fuzzy rules. Then some new scale-limited criteria of global exponential stability in Lagrange sense are obtained for FMNNs with bounded feedback functions on the basis of inequalities on time scales and inequality scaling techniques. Also, novel criteria for Lurie-type feedback functions are given, which mainly employ the constructed scale-limited generalized Halanay inequality. Moreover, by matrix-norm strategies, some matrix-norm-based scale-limited criteria are derived for bounded and Lurie-type feedback functions, respectively. It also can be seen that the matrix-norm-based criteria are in accordance with the matrix-measure-based conditions provided the time scale is specified as real set. All scale-limited criteria for Lagrange stability not only include continuous-time criteria and its discrete-time analogues, but also contain more complex cases such as the arbitrary combination of them. In the end, some numerical simulations exhibit the validity of the obtained results.

关键词： Lagrange stability memristive neural networks (MNNs) Takagi-Sugeno (T-S) fuzzy logics time scale

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Remaining Useful Life Prediction for a Multi-stack Solid Oxide Fuel Cell System with Degradation Interactions

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CSEE Journal of Power and Energy Systems 2022年第4期8卷 1207-1214页

作者： Xiaojuan Wu Liangfei Xu Yang Huang Danan Yang Junhao Wang Houjun Wang Xi Li School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 610054China State Key Lab of Automotive Safety and Energy School of Vehicle and MobilityTsinghua UniversityBeijing 100084China School of Artificial Intelligencei and Automation Key Laboratory of Image Processing and Intelligent Control of Education MinistryHuazhong University of Science and TechnologyWuhan 430074China

Due to the constraints of manufacturing and materials,high-power plants cannot rely on only one solid oxide fuel cell stack.A multi-stack system is a solution for a highpower system,which consists of multiple fuel cell stacks.A short lifetime is one of the main challenges for the fuel cell before largescale commercial applications,and prognostic is an important method to improve the reliability of fuel *** from the traditional prognostic approaches applied to single-stack fuel cell systems,the key problem in multi-stack prediction is how to solve the correlation of multi-stack degradation,which can directly affect the accuracy of *** response to this difficulty,a standard Brownian motion is added to the traditional Wiener process to model the degradation of each stack,and then the probability density function of the remaining useful life(RUL)of each stack is ***,a Copula function is adopted to reflect the dependence between life distributions,so as to obtain the remaining useful life for the whole multi-stack system.1 The simulation results show that compared with the traditional prediction model,the proposed approach has a higher prediction accuracy for multi-stack fuel cell systems.

关键词： Degradation interaction multi-stack remaining useful life(RUL) solid oxide fuel cell(SOFC)

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Exponential synchronization of coupled memristive neural networks with time delays

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NEURAL COMPUTING & APPLICATIONS 2014年第6期24卷 1421-1430页

作者： Wang, Guan Shen, Yi Huazhong Univ Sci & Technol Dept Control Sci & Engn Wuhan 430074 Hubei Peoples R China Minist China Key Lab Image Proc & Intelligent Control Educ Wuhan 430074 Hubei Peoples R China

In this paper, the model of coupled memristive neural networks with time delays is established, and sufficient conditions are obtained that guarantee the exponential synchronization for such system. Memristive network exhibits state-dependent switching behaviors due to the physical properties of memristor. It is demonstrated that the synchronization performance is largely dependent on the coupling pattern and strength among memristive neural networks. Moreover, the information exchange graph of the underlying network topology need not be undirected or strongly connected. Finally, numerical simulations are given to verify the usefulness and effectiveness of our results.

关键词： Exponential synchronization Memristor Coupled neural networks Time delays State-dependent switching

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Multi-attribute statistics histograms for accurate and robust pairwise registration of range images

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NEUROCOMPUTING 2017年 251卷 54-67页

作者： Yang, Jiaqi Zhang, Qian Cao, Zhiguo Huazhong Univ Sci & Technol Guangdong Prov Key Lab Digital Mfg Equipment Educ Minist ChinaGuangdong HUST Ind Technol Res Image Proc & Intelligent Control Key LabSch Auto Wuhan Peoples R China

Registration of range images based on local shape features is widely adopted due to its validated effectiveness and robustness, while most existing local shape descriptors struggle to simultaneously achieve a pleasurable and balanced performance in terms of distinctiveness, robustness and time efficiency. This paper proposes a novel representation of 3D local surfaces, called multi-attribute statistics histograms (MaSH), for automatic registration of range images. MaSH comprises both spatial and geometric information characterizations. The characterization of spatial information is achieved via radial partitions in the 3D local support volume around the keypoint based on a local reference axis (LRA), creating a set of subspaces. While the encoding the shape geometry is performed by calculating statistical histograms of multiple faint correlated geometric attributes (i.e., local depth, normal deviation, and surface variation angle) for each subspace, so as to achieve information complementarity. Then, a robust rigid transformation estimation algorithm named 2-point based sample consensus with global constrain (2SAC-GC) is presented to tackle the problem of calculating an optimal transformation from the correspondence set with outliers. Finally, a coarse-to-fine registration method based on MaSH and 2SAC-GC is proposed for aligning range images. Experiments on both high-resolution (Laser Scanner) and low-resolution (Kinect) datasets report that, our method achieves a registration accuracy of 90.36% and 80.39% on the two datasets, respectively. It also exhibits strong robustness against noise and varying mesh resolutions. Furthermore, feature matching experiments show the over-all superiority of the proposed MaSH descriptor against the state-of-the-arts including the spin image, snapshots, THRIFT, FPFH, RoPS, LFSH and RCS descriptors. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Local reference axis Multi-attribute Transformation estimation Feature matching Range image registration

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Solving the traveling salesman problem based on an adaptive simulated annealing algorithm with greedy search

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APPLIED SOFT COMPUTING 2011年第4期11卷 3680-3689页

作者： Geng, Xiutang Chen, Zhihua Yang, Wei Shi, Deqian Zhao, Kai 202 Inst China Ordnange Ind Xianyang 712099 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Dept Control Sci & Engn Wuhan 430074 Peoples R China

The traveling salesman problem (TSP) is a classical problem in discrete or combinatorial optimization and belongs to the NP-complete classes, which means that it may be require an infeasible processing time to be solved by an exhaustive search method, and therefore less expensive heuristics in respect to the processing time are commonly used in order to obtain satisfactory solutions in short running time. This paper proposes an effective local search algorithm based on simulated annealing and greedy search techniques to solve the TSP. In order to obtain more accuracy solutions, the proposed algorithm based on the standard simulated annealing algorithm adopts the combination of three kinds of mutations with different probabilities during its search. Then greedy search technique is used to speed up the convergence rate of the proposed algorithm. Finally, parameters such as cool coefficient of the temperature, the times of greedy search, and the times of compulsive accept and the probability of accept a new solution, are adaptive according to the size of the TSP instances. As a result, experimental results show that the proposed algorithm provides better compromise between CPU time and accuracy among some recent algorithms for the TSP. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Simulated annealing Greedy search Traveling salesman problem Adaptive Combinatorial optimization Heuristic

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Model Predictive control Method for Multi-motor System with Dead Zone 6

Model Predictive Control Method for Multi-motor System with ...

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6th International Conference on Automation, control and Robotics Engineering (CACRE)

作者： Fan, Genglin Tang, Xiuchuan Shen, Yi Deng, Linan Huazhong Univ Sci & Technol China EU Inst Clean & Renewable Energy Key Lab Image Proc & Intelligent Control Wuhan Peoples R China Huazhong Univ Sci & Technol Sch Mech Sci & Engn Key Lab Image Proc & Intelligent Control Wuhan Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan Peoples R China

ISBN: (纸本)9781665435765

The multi-motor system shows excellent performance in achieving high-precision control in the applications with large load inertia, such as large-aperture telescopes and high-precision processing machine tools. However, the non-linearity of gear transmission remains a key challenge that will cause the fluctuation of angular velocity and position of the load in the multi-motor system. In order to compensate for the non-linearity in the multi-motor system, this paper introduces a dead-zone model into the spring-damper dynamics of the multi-motor system, based on which a model predictive control (MPC) method is proposed to control the angular velocity and angle of the load. The optimization target of the proposed controller is to limit the fluctuations of input torque as much as possible. The effectiveness of the dead-zone based dynamic model and the MPC method are verified by simulation.

关键词： multi-motor system MPC dead zone

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On-line estimation of image jacobian matrix by improved broyden's method in uncalibrated visual servoing

On-line estimation of image jacobian matrix by improved broy...

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Conference on Pattern Recognition and Computer Vision

作者： Zeng, Xiangjin Huang, Xinhan Wang, Min Huazhong Univ Sci & Technol Dept Control Sci & Engn Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

ISBN: (纸本)9780819469526

A novel improved broyden's method has been presented to estimate image jacobian matrix for uncalibrated visual servoing. In this paper, we apply chebyshev polynomial as a cost function to approximate best value. Compared with recursive least square (RLS) algorithm which is restricted by the prior knowledge for obtaining some performances, chebyshev polynomial algorithm has a great adaptability to estimate jacobian parameter, even without the prior knowledge. A microscopic image jacobian model has been developed for the four degree-of-freedom micromanipulator in our microassembly system. The performance has been confirmed by simulations and experiments.

关键词： image jacobian matrix broyden' method chebyshev RLS uncalibrated visual servoing

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Dynamic Integral Sliding Mode for Launch Vehicle Attitude control System

Dynamic Integral Sliding Mode for Launch Vehicle Attitude Co...

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24th Chinese control and Decision Conference (CCDC)

作者： Wang, Zirui Liu, Lei Wang, Yongji Wang, Zhishen Huazhong Univ Sci & Technol Dept Control Sci & Engn Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

ISBN: (纸本)9781457720727

As it is known that launch vehicle is facing a very harsh environment during the fight process. The challenge of various perturbations and uncertainties has lead to many traditional control methods' failure to meet the requirements of attitude control system. Due to the main advantage of sliding mode control's robustness to the system uncertainties and disturbances in the so-called sliding mode, it has been widely used in engineering. In this paper, regarding particularly on chattering problem, the authors developed a novel dynamic integral sliding mode control scheme and the comparative simulation results carried out with traditional dynamic integral sliding mode demonstrates the superiority of the newly designed control law.

关键词： Launch vehicle Attitude control Dynamic integral sliding mode control

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The Separation Property Enhancement of Liquid State Machine by Particle Swarm Optimization

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6th International Symposium on Neural Networks

作者： Huang, Jiangshuai Wang, Yongji Huang, Jian Huazhong Univ Sci & Technol Dept Control Sci & Engn Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

ISBN: (纸本)9783642015120

The separation property of Liquid State Machine (LSM) is a key for its power of computing, but the weights and delays of the inter-connections in the spiking neural circuit are usually randomly created and kept unchanged. which hinders the performance of the LSM greatly. In this paper. particle swarm optimization (PSO) was applied to optimize the weights and delays of the circuit so as to enhance the separation property of the LSM. Separation of random spike trains and Fisheriris data-set classification experiments are done by the optimized circuit. Demonstration examples show that the PSO can enlarge the separation property of the circuit greatly compared to the normal Hebbian-learning algorithm and enhance the computing ability of LSM.

关键词： Liquid state machine Particle swarm optimization Separation property

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