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On the periodic dynamics of memristor-based neural networks with time-varying delays

Information Sciences 2014年 279卷 358-373页

作者： Jiejie Chen Zhigang Zeng Ping Jiang School of Automation Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Information Processing and Intelligent Control Ministry of Education Wuhan 430074 China

In this paper, we study the existence, uniqueness and stability of periodic solution for a wide class of memristor-based neural networks with time-varying delays. By employing the topological degree theory in set-valued analysis, differential inclusions theory and a new Lyapunov function method, we prove that the neural network has a unique periodic solution, which is globally exponentially stable. Moreover, we prove the existence, uniqueness and global exponential stability of equilibrium point for time-varying delayed memristor-based neural networks with constant coefficients. The obtained results improve and extend previous works on memristor-based or usual neural network dynamical systems with continuous or discontinuous right-hand side. Finally, two numerical examples are provided to show the applicability and effectiveness of our main results.

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3-D temperature field reconstruction of lithium-ion battery pack using real-time distributed moving horizon estimation

3-D temperature field reconstruction of lithium-ion battery ...

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第35届中国控制与决策会议

作者： Jiayu Yan Yiming Wan School of Artificial Intelligence and Automation Huazhong University of Science and Technologyand Key Laboratory of Image Processing and Intelligent ControlMinistry of Education

As lithium-ion batteries are widely used in different fields,the thermal effect is of serious *** to achieve accurate temperature estimation in real time is the main challenge of current *** address this problem,we propose a realtime distributed moving horizon estimation(RT-DMHE) based on partial differential equations describing thermal dynamics of a lithium-ion battery *** decomposes the real-time centralized moving horizon estimation(RT-CMHE) into multiple local estimators that run in parallel with information exchange from adjacent *** validation shows that the root mean square error of temperature estimates from the proposed RT-DMHE is smaller than that of an existing distributed Kalman filter in ***,compared to the RT-CMHE,the proposed RT-DMHE achieves comparable estimation accuracy while vastly reducing the average computation time per sample.

关键词： lithium-ion battery pack distributed moving horizon estimation real-time computation state-of-temperature estimation

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Thermal Safety Analysis and Dynamic control Strategy for Mode Switching Process of Reversible Solid Oxide Cell System

Thermal Safety Analysis and Dynamic Control Strategy for Mod...

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第42届中国控制会议

作者： Wei Zhao Guoqiang Liu Zexin Li Xi Li School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education MinistryHuazhong University of Science and Technology

Reversible solid oxide cells(rSOC) can operate in both electrolysis mode and in fuel cell mode with high efficiency and reduced cost using the same device for both *** used in dynamic operation with intermittent electrical power sources,rSOC system switches from the fuel cell(SOFC) to electrolyzer(SOEC) and vice versa depending on load and grid *** can lead to temperature profiles within the stack that can potentially lead to the failure of the stack and eventually the *** the present work,a system-level dynamic model of r SOC is established and validated against experimental ***,detailed dynamic thermal behavior of stack during the switching between the two modes is analyzed,and a temperature management controller based on Model Predict control method(MPC) is *** flow and temperature at the stack inlet are controlled by air flow and bypass valves,avoiding problems associated with temperature overshoot during transient *** simulation results show that the temperature controller has the ability to follow fast thermal changes while maintaining thermal safety,which indicates the competitiveness of the controller.

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Decoupling guaranteed cost control of BTT vehicle based on LMI

Decoupling guaranteed cost control of BTT vehicle based on L...

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IEEE International Conference on intelligent Computing and intelligent Systems (ICIS)

作者： Zhixiang Deng Yongji Wang Lei Liu Chuanfeng Li Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781424447374;9781424447541

This paper presents a new approach for coupling control problems for norm bounded continuous-time uncertain systems. Firstly, a design of the state feedback decoupling controller is presented. The nominal model could be decoupled completely and the coupling of the actual system would be reduced. Secondly, based on the linear matrix inequality (LMI), combining the guaranteed cost control law with the decoupling control, the state feedback tracking guaranteed cost control law is proposed. Finally, taking BTT vehicle as the research objective, the design procedure of the decoupling guaranteed cost controllers is shown and the final results of the simulation are proved with effectiveness for the proposed design approach.

关键词： Costs Vehicles control systems Uncertain systems Robust control State feedback Linear matrix inequalities Linear feedback control systems Uncertainty Missiles

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Constrained trajectory optimization using migrant particle swarm optimization algorithm

Constrained trajectory optimization using migrant particle s...

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International Conference on Bio-Inspired Computing: Theories and Applications, BICTA

作者： Fuqiang Xie Yongji Wang Zongzhun Zheng Da Zhang Department of Control Science and Engineering Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

A novel PSO algorithm, the Migrant Particle Swarm Optimization (Migrant PSO), is presented to solve the trajectory optimization problem in the presence of constraints such as dynamic pressure and overload. Imitating the behaviour of a flock of migrant birds, the Migrant PSO algorithm employs stochastic search method and adaptive linear search method respectively for PSO search spaces including both continuous space and discrete space. In the example of the minimum peak heat rate reentry trajectory optimization for X-33 vehicle model with free terminal time, some key problems such as parameterized method are argued in detail. The simulation results indicate that the Migrant PSO algorithm proves to be able to generate a complete and optimal 3DOF reentry trajectory rapidly.

关键词： Constraint optimization Particle swarm optimization Stochastic processes Ant colony optimization Optimization methods Search methods Space vehicles Pressure control Birds Optimal control

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Parallel Generate Entry Landing Footprint Using Differential Evolution

Parallel Generate Entry Landing Footprint Using Differential...

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International Symposium on Computer, Consumer and control (IS3C)

作者： Songtao Chang Yongji Wang Lei Liu Department of Control Science and Engineering Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

Landing footprint of an entry vehicle provides critical information for mission planning. Conventional methods calculate it through solving a family of multi-constraints optimal control problems. It is difficult to solve. To generate the boundary of it, we proposed a new scheme based on differential evolution(DE). Utilizing DE's parallelism, each run generates one side instead of one point of the boundary. To get the full boundary, just need run the algorithm two times. The algorithm's merits include accurate, fast, not relying on simplification of the system, all control variables are under consideration and facilitating parallel programming.

关键词： Vehicles Vehicle dynamics Optimal control Vectors Trajectory Optimization Heuristic algorithms

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Spatial filtering for brain computer interfaces: A comparison between the common spatial pattern and its variant

arXiv

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arXiv 2018年

作者： He, He Wu, Dongrui Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan China

The electroencephalogram (EEG) is the most popular form of input for brain computer interfaces (BCIs). However, it can be easily contaminated by various artifacts and noise, e.g., eye blink, muscle activities, powerline noise, etc. Therefore, the EEG signals are often filtered both spatially and temporally to increase the signal-to-noise ratio before they are fed into a machine learning algorithm for recognition. This paper considers spatial filtering, particularly, the common spatial pattern (CSP) filters for EEG classification. In binary classification, CSP seeks a set of filters to maximize the variance for one class while minimizing it for the other. We first introduce the traditional solution, and then a new solution based on a slightly different objective function. We performed comprehensive experiments on motor imagery to compare the two approaches, and found that generally the traditional CSP solution still gives better results. We also showed that adding regularization to the covariance matrices can improve the final classification performance, no matter which objective function is used. Copyright © 2018, The Authors. All rights reserved.

关键词： Brain computer interface

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Extended state observer based non-iteration predicted entry guidance

Extended state observer based non-iteration predicted entry ...

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International Conference on Modelling, Identification and control (ICMIC)

作者： Songtao Chang Mao Su Da Zhang Yongji Wang Department of Control Science and Engineering Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

It is difficult to guide the entry vehicle to prescribed area due to the disperse of environment and kinematics. Through predicted residual range at the current state based on drag acceleration, we developed a predictor-corrector guidance law which doesn't need iteration to figure out the reference trajectory. Then using extended state observer based controller to track the reference trajectory. We use several missions(under various disperse conditions) to test the guidance law. Simulation results demonstrated that the guidance law is able to achieve the prescribed terminal conditions under various perturbations in the aerodynamic coefficients, the density of the atmosphere and the mass of the vehicle.

关键词： Acceleration Trajectory Vehicles Observers Vehicle dynamics Planning Earth

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MIME-KNN: Improve KNN Classifier Performance Include Classification Accuracy and Time Consumption

MIME-KNN: Improve KNN Classifier Performance Include Classif...

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2018 International Conference on Computer Science and Software Engineering (CSSE 2018)

作者： Taizhang Shang Xiang Xia Jun Zheng School of Automation Huazhong University of Science and Technology (HUST) Key Laboratory of Image Information Processing and Intelligent Control Ministry of Education

The K Nearest Neighbor(KNN) classifier has been widely used in the applications of data mining and machine learning, because of its simple implementation and distinguished performance. However, because the distance between all training samples and test samples have to be calculated, when there are too many samples or samples have huge features dimensionality, the time complexity and space complexity are high. The paper proposes a KNN algorithm with the minimum intra-class distance and the maximum extra-class distance(MIME-KNN). By finding a transformation matrix, the algorithm minimizes the intra-class distance and maximizes the distance between classes, which can improve the classification performance of traditional KNN algorithm. At the same time, the algorithm will also reduce the dimensionality of the samples to achieve the purpose of reducing time and space complexity. Experimental results show that the MIME-KNN work well in practical.

关键词： MIME-KNN Improve KNN Classifier Performance Include Classification Accuracy and Time Consumption

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Adaptive event-triggered consensus for multi-agent systems with stochastic switching topologies and delays

Adaptive event-triggered consensus for multi-agent systems w...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Dong Yue Xiuxia Yin Department of Control Science and Engineering and the Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781467351942

This paper is concerned with the consensus problem for a class of Lipschitz nonlinear agents with Markov switching topologies and time-varying delays. The distributed event-triggered consensus control with an adaptive law in adjusting the coupling weights between neighboring agents is designed, which can not only guarantee the consensus performance in the mean square sense but also reduce the communication burden since the introduction of the event-triggered communication scheme. Different from the traditional event-triggers in the existing references, the parameter of the event-trigger in this paper is adaptively adjusted by using an adaptive law. A convincing simulation example is given to illustrate the theoretical results.

关键词： multi-agent system (MAS) adaptive event-triggered control random switching topology LMI Event trigger Self tuning Interim Local Management Interface Multi-agent systems Stochastic topology Markov

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