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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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Rapid trajectory optimization based on Migrant PSO

Rapid trajectory optimization based on Migrant PSO

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

作者： Fuqiang Xie Yongji Wang Chuanfeng Li Dangjun Zhao 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

ISBN: (纸本)9781424447374;9781424447541

This paper proposes a rapid trajectory optimization approach using a novel PSO algorithm, the Migrant particle swarm optimization (Migrant PSO). Imitating the behavior 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 control energy 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： Birds Stochastic processes Search methods Optimization methods Space technology Particle swarm optimization Vehicles Design optimization Programmable control Adaptive control

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Active Disturbance Rejection Guidance for Ascent Using Quadratic Transition

Active Disturbance Rejection Guidance for Ascent Using Quadr...

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International Symposium on Computer, Consumer and control (IS3C)

作者： Xuefang Lu Yongji Wang 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

This paper presents an active disturbance rejection guidance method using quadratic transition for the atmospheric ascent guidance problem. The quadratic transition is designed from the current flight states with a reference trajectory planned off-board. For any states error, the solution of the designed quadratic transition converges to the reference trajectory. The guidance command is obtained from the derivative of the designed quadratic transition. For the unknown modeling error, the guidance command is compensated using the estimated disturbances from the extended state observer. Computer simulation for GHV (Generic Hypersonic Air Vehicle) model, which includes initial states error and modeling error, shows great accuracy and effectiveness of this guidance method.

关键词： Trajectory Atmospheric modeling Computational modeling Aerodynamics Vehicles Observers Accuracy

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Channel and Trials Selection for Reducing Covariate Shift in EEG-based Brain-Computer Interfaces

Channel and Trials Selection for Reducing Covariate Shift in...

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IEEE International Conference on Systems, Man, and Cybernetics

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

ISBN: (纸本)9781728145709

This paper aims at reducing the calibration effort of EEG-based brain-computer interfaces (BCIs). More specifically, in the context of cross-subject classification, we correct covariate shift of EEG data from different subjects, so that a classifier trained on auxiliary subjects can also be applied to a new subject, without any labeled trials from the new subject. Methods: We propose two approaches to enhance the performance of a state-of-the-art Riemannian space transfer learning (TL) algorithm: 1) trials selection, which resamples trials from the auxiliary subjects so that they become more consistent with those of the new subject;and, 2) channel selection, which reduces the number of channels and hence makes the Riemannian space computations more accurate and efficient. Results: We tested the proposed approaches on two motor imagery datasets. The results verified that they can enhance the performance of the state-of-the-art TL algorithm. Conclusion and significance: Our proposed approaches make the state-of-the-art TL algorithm more effective and efficient.

关键词： Brain-Computer Interfaces experimentation Trials Computer interfaces Thallium Shift Classifiers biological control 2-channel

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Modeling of Solid Oxide Electrolysis Cell with Oxygen Pressure at the Oxygen electrode/Electrolyte Interface

Modeling of Solid Oxide Electrolysis Cell with Oxygen Pressu...

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第34届中国控制与决策会议

作者： Zhiping Xia Xi Li School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education MinistryHuazhong University of Science & Technology

As one of the key degradation mechanisms of Solid oxide electrolysis cell(SOEC),oxygen electrode delamination directly affects the durability of *** order to improve the service life of SOEC stack,optimizing the system regulation range is an effective *** this study,according to the delamination mechanism of SOEC oxygen electrode,based on the existing thermal and electrical characteristics of the SOEC stack,a new gas characteristic of oxygen electrode/electrolyte interface oxygen pressure is added,and a cross-flow SOEC 2-D stack model with the oxygen electrode/electrolyte interface oxygen pressure was ***,the influence of the oxygen electrode/electrolyte interface oxygen pressure characteristics on the safe operating range of the stack is *** simulation results show that the safe operating range of the system was optimized by adding it.

关键词： Solid oxide electrolysis cell Durability Delamination mechanism 2-D model Advantage analysis

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