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A Fuzzy Optimal Sliding-Mode Guidance for Intercepting Problem

IFAC Proceedings Volumes 2014年第3期47卷 3401-3406页

作者： Zhiwei Hou Mao Su Yongji Wang Lei Liu School of Automation Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

In this paper, a novel terminal guidance law is proposed to solve the problem of exo-atmospheric interception. It is designed based on the proportional navigation (PN) and the classical optimal sliding-mode guidance (OSMG). It overcomes the shortcoming of these two traditional guidance laws and inherits their merits. Particularly, in the scenario of exoatmospheric interception, when the maneuvering information of the targets are unavailable , the proposed guidance law has superior performance than the traditional guidance law. Briefly, to enhance the interceptive performance, we introduce the optimal control and sliding-mode control methods to the guidance law for maneuvering target's interception. On the other hand, the traditional proportional navigation law is introduced to intercept the target with a constant speed. After that, a fuzzy switching function is provided to harmonize both situations above, according to the real-time estimation of maneuver. To guarantee the stability of the law, a Lyapunov based condition is obtained. Finally, different from the two-dimensional simulation in most of the literatures of terminal guidance law researches, we illustrate our method in the nonlinear discrete three-dimensional simulation environment by the Runge-Kutta method. Compared with the pure OSMG and PN, the proposed law performs better.

关键词： Terminal guidance Optimal control Sliding-mode control Fuzzy control Lyapunov stability

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On string languages generated by sequential spiking neural P systems based on maximum spike number 1

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13th International Conference on Unconventional Computation and Natural Computation, UCNC 2014

作者： Jiang, Keqin Zhang, Yuzhou Pan, Linqiang Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan 430074 Hubei China School of Computer and Information Anqing Normal University Anqing 246133 Anhui China

ISBN: (数字)9783319081236

ISBN: (纸本)9783319081229

Spiking neural P systems (SN P systems, for short) are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes. In this work, we consider SN P systems with the restriction: at each step the neuron with the maximum number of spikes among the neurons that can spike will fire (if there is a tie for the maximum number of spikes stored in the active neurons, only one of the neurons containing the maximum is chosen non-deterministically). We investigate the computational power of such sequential SN P systems that are used as language generators. We prove that recursively enumerable languages can be characterized as projections of inverse-morphic images of languages generated by that sequential SN P systems. The relationships of the languages generated by these sequential SN P systems with finite and regular languages are also investigated. © 2014 Springer International Publishing Switzerland.

关键词： Neurons

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H ∞ based decoupling tracking control of hypersonic vehicle

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IFAC Proceedings Volumes 2014年第3期47卷 894-899页

作者： Xuejing Lan Zhishen Wang Lei Liu Yongji Wan School of Automation Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

The H ∞ based decoupling tracking control is studied in this paper. A virtual system constituted by the controlled system and the no coupling reference model is firstly set up. The controlled system is driven to follow the reference model to realize the decoupling. And the tracking error can be formulated by the H ∞ norm of the virtual system. Then the controller is derived by minimizing the H ∞ norm, which can be described by Linear Matrix Inequalities (LMIs). The necessary and sufficient condition of existence of controller is derived based on the LMIs above. A flight control example is given to illustrate the effectiveness of the proposed method. The simulation results show that the proposed method is of better control performance than Linear Quadratic (LQ) tracking controller.

关键词： decoupling control reference model H ∞ LMI hypersonic vehicle

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Changes in brain functional network connectivity after stroke

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Neural Regeneration Research 2014年第1期9卷 51-60页

作者： Wei Li Yapeng Li Wenzhen Zhu Xi Chen Key Laboratory of Image Processing and Intelligent Control Ministry of Education Department of Control Science and Engineering Huazhong University of Science and Technology Department of Radiology Tongji HospitalTongji Medical CollegeHuazhong University of Science and Technology

Studies have shown that functional network connection models can be used to study brain net- work changes in patients with schizophrenia. In this study, we inferred that these models could also be used to explore functional network connectivity changes in stroke patients. We used independent component analysis to find the motor areas of stroke patients, which is a novel way to determine these areas. In this study, we collected functional magnetic resonance imaging datasets from healthy controls and right-handed stroke patients following their first ever stroke. Using independent component analysis, six spatially independent components highly correlat- ed to the experimental paradigm were extracted. Then, the functional network connectivity of both patients and controls was established to observe the differences between them. The results showed that there were 11 connections in the model in the stroke patients, while there were only four connections in the healthy controls. Further analysis found that some damaged connections may be compensated for by new indirect connections or circuits produced after stroke. These connections may have a direct correlation with the degree of stroke rehabilitation. Our findings suggest that functional network connectivity in stroke patients is more complex than that in hea- lthy controls, and that there is a compensation loop in the functional network following stroke. This implies that functional network reorganization plays a very important role in the process of rehabilitation after stroke.

关键词： nerve regeneration brain injury stroke motor areas functional magnetic resonanceimaging brain network independent component analysis functional network connectivity neuralplasticity NSFC grant neural regeneration

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A novel method to derive ambulatory blood pressure from the radial pressure waveform

Communications in Computer and Information Science

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Communications in Computer and Information Science 2014年 472卷 176-181页

作者： He, Long Chen, Zhihua Zhang, Zheng Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan Hubei China

ISBN: (纸本)9783662450482

In this paper, we develop a novel application of independent component analysis (ICA) based auto-regression forecasting model(ICAARF). The method can noninvasively, continuously and conveniently derive ambulatory blood pressure (ABP) from the radial artery pressure waveform (RAPWF). To eliminate the effect of correlative factors in measurement, the ICA method is used to decomposite the raw signal and extract the independent component affected by blood pressure (BP). Based on the spectrum density of independent component, an auto-regression forecasting model is set up to derive BP. Experimental results show an excellent correlation and agreement with the BP measured by Omron electronic BP monitor (Type: HEM-7012). If the ICA-ARF is used, the the error can be reduced from 7.4mmHg to 2.55mmHg. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Blood pressure

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A novel ANN-based harmonic extraction method tested with ESN, RNN and MLP in shunt active power filters

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International Journal of Wireless and Mobile Computing 2014年第2期7卷 123-131页

作者： Xu, Jinbang Yang, Jun Shen, Anwen Chen, Junfeng Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

With the wide use of power conversion devices - 'nonlinear loads' - many harmonic currents are being injected into the power grid. Shunt Active Power Filters (SAPF) are the power electronic equipment to compensate the harmonic currents caused by nonlinear loads. As the foundation of the harmonics recognition and compensation, harmonic extraction is the key technology in SAPF. Artificial Neural Networks (ANN) method has the features of parallel computation and satisfactory results for distorted source voltages over traditional extraction methods. This paper proposes a new harmonic extraction method based on ANN. To test the feasibility of different types of neural networks in this application, this paper compares the performances of three types of ANN: Echo State Networks (ESN), Recurrent Neural Networks (RNN) and Multilayer Perceptron Networks (MLP). © 2014 Inderscience Enterprises Ltd.

关键词： Extraction

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On string languages generated by spiking neural P systems with astrocytes

Communications in Computer and Information Science

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Communications in Computer and Information Science 2014年 472卷 225-229页

作者： Kong, Yuan Zhang, Zheng Liu, Yang Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan Hubei430074 China

ISBN: (纸本)9783662450482

Spiking neural P systems with astrocytes (SNPA systems, for short) are a class of distributed parallel computing devices inspired from the way spikes pass through the synapses between the neurons. In this work, we investigate the language generation power of SNPA systems. Specifically, we prove that SNPA systems without the forgetting rules can generate recursively enumerable languages and characterize regular languages. Furthermore, we give a finite language that can be generated by SNPA systems, but which cannot be generated by spiking neural P systems without astrocytes. These results show that astrocyte is a powerful ingredient for generating languages by spiking neural P systems. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Distributed computer systems

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Adaptive pinning cluster synchronization of fractional-order complex dynamical networks

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Applied Mathematics and Computation 2014年 231卷 347-356页

作者： Guan-Sheng Wang Jiang-Wen Xiao Yan-Wu Wang Jing-Wen Yi School of Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 PR China

The problem about cluster synchronization of fractional-order CDNs is studied via a pinning adaptive approach in this paper. Based on the stability theory of fractional differential equations, some sufficient criteria for local and global cluster synchronization of fractional-order CDNs are derived. In this paper, the coupling configuration matrix can be asymmetric as well as reducible and the inner coupling matrix can also be asymmetric. Moreover, the number of pinning nodes in each cluster can be evaluated. Especially, when the coupling strength is large enough and the coupling configuration matrix is symmetric, cluster synchronization can be achieved via pinning a single node in each cluster. Finally, some typical examples are given to illustrate the correctness and effectiveness of our results, a surprising finding is that the synchronization performance will become better as the fractional order decreases in this simulation.

关键词： Complex dynamical networks Cluster synchronization Fractional-order Pinning adaptive control

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DISCOVERING DISTINCTIVE ACTION PARTS FOR ACTION RECOGNITION

DISCOVERING DISTINCTIVE ACTION PARTS FOR ACTION RECOGNITION

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IEEE International Conference on image processing

作者： Feifei Chen Nong Sang Changxin Gao Xiaoqin Kuang Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology

ISBN: (纸本)9781479957521

Recent methods based on mid-level visual concepts have shown promising capability in human action recognition field. Automatically discovering semantic entities such as parts for an action class remains challenging. In this paper, we focus on discovering distinctive action parts for recognition of human actions by learning and selecting a small number of discriminative part detectors directly from training videos. We initially train a large collection of candidate Exemplar-LDA detectors from clusters obtained by clustering spatiotemporal patches in whitened space. A novel Coverage-Entropy curve is proposed as a means of measuring the representative and discriminative capabilities of part detectors, and used to select a set of compact and meaningful detectors out of the vast candidates. By integrating these mined detectors into "bag of parts" representation, our approach demonstrates state-of-the-art performance on the UCF50 dataset.

关键词： Action recognition Action part Exemplar LDA

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Multiple neural networks switched prediction for landslide displacement

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Engineering Geology 2014年 186卷 91-99页

作者： Lian, Cheng Zeng, Zhigang Yao, Wei Tang, Huiming School of Automation Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China School of Computer Science South-Central University for Nationalities Wuhan 430074 China Faculty of Engineering China University of Geosciences Wuhan 430074 China

An accurate prediction of landslide displacement is challenging and of great interest to governments and researchers. In order to reduce the risk of selecting the types of influencing factors and artificial neural networks (ANNs), a multiple ANNs switched prediction method is proposed for landslide displacement forecasting. In the first stage, a set of individual neural networks are developed based on different environmental factors and/or different training algorithms. In the second stage, a switched prediction method is used to select the appropriate individual neural network for prediction purpose. For verification and testing, three typical landslides in Three Gorges Reservoir, namely Baishuihe landslide, Bazimen landslide and Shiliushubao landslide, are presented to test the effectiveness of our method. Application results demonstrate that the proposed method can significantly improve model generalization and perform similarly to, or better than, the best individual ANN predictor. © 2014 Elsevier B.V.

关键词： Forecasting

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