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第25届中国控制与决策会议

作者： Bing Liu Zhen Chen Xiangdong Liu Fan Yang School of Automation Beijing Institute of Technology Key Laboratory for Intelligent Control & Decision of Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781467355322

This paper presents a new method based on the polytopic linear differential inclusion and the robust mixed H2/∞ filtering for the design of the nonlinear filter with non-Gaussian noises. The main goal is to solve the problems of the complexity and large calculation number in the general nonlinear filter and the filtering design problem for systems with the non-Gaussian noises. The noises considered in the paper involve two different kinds of noises: white noises and energy bounded noises. Differing from the linearization in most nonlinear filters, the estimation error system for the nonlinear system is represented by an uncertain polytopic linear model, based on which, the rectification equations for the predicted errors are designed following the robust mixed H2/∞ filtering. The state estimates for the nonlinear system are given through updating the predictions by the rectified quantities, where, the state predicted quantities of the nonlinear system are gained by the prediction equation of the EKF. The evident advantage of the new filter is the filter coefficients of the rectification equation are constant, without the need to evaluate the Jacobian matrixes. As a result, the calculation number for the new filter is decreased much and the real-time performance of the new filter is much better than the EKF, though the accuracy is a little decline. Its effectiveness is demonstrated by using an example and the statistics result of the calculation number for the filters in the example.

关键词： nonlinear filter polytopic linear inclusion non-Gaussian noise

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Global MPPT for PV systems under partially shaded conditions based on voltage band

Global MPPT for PV systems under partially shaded conditions...

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Chinese control Conference (CCC)

作者： Fan Xinyu Fang Deng Fengmei Li Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing P. R. China School of Automation Beijing Institute of Technology Beijing P. R. China Beijing Institute of Technology Beijing Beijing CN

This paper presents a novel maximum power point (MPP) tracking (MPPT) method to increase photovoltaic (PV) system performance during partially shaded conditions (PSCs). The method is based on voltage scanning method. Voltage band method and restricted voltage scanning method is used to increase the scanning speed. A method is proposed to determine whether partial shading occurs. The main advantage of the proposed method is the ability to search the global peak fast. Simulation results shows the good performance of proposed method.

关键词： Maximum power point trackers Photovoltaic systems Arrays Solar energy Mathematical model Equations

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Study on GIS's application in driving in the unstructured environment for UGV

Study on GIS's application in driving in the unstructured en...

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2013 International Conference on Geo-Informatics in Resource Management and Sustainable Ecosystem, GRMSE 2013

作者： Yang, Qiangrong Wang, Meiling School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Intelligent Control and Decision of Complex System Beijing 100081 China

ISBN: (纸本)9783642419072

For UGV, driving in the unstructured environment safely and quickly without human intervention becomes increasingly important. While many scholars have conducted researches in driving in this case, the results seem quite unsatisfied. In this paper, how to use GIS in aiding the UGV to drive in the unstructured environment is studied. First, GIS is used to process the raw data received from the 3D laser scanner to get the high-resolution gradient and elevation grid, which is used to determine the traversability of the environment. Then the relatively low-resolution gradient grid is used as the cost field in the path planning algorithm to generate the optimal path from the start point to the goal point. At last, an algorithm is introduced to get the reference speed limit from the given optimal path according to the geometry features of the path and the gradient grid. Simulation and experiment results are given to show the effectiveness of the algorithms. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Motion planning

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SDRE based Optimal Time-Varying Sliding Mode control for Re-entry Vehicle

SDRE based Optimal Time-Varying Sliding Mode Control for Re-...

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第25届中国控制与决策会议

作者： Liang Wang Yongzhi Sheng Xiangdong Liu Jie Geng School of Automation Beijing Institute of Technology Key laboratory for Intelligent Control & Decision of Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781467355339

An optimal time-varying sliding mode controller based on SDRE approach is proposed in this paper for re-entry vehicle attitude control in the presence of parametric uncertainties and external disturbances. Firstly, an optimal time-varying sliding surface is obtained through the minimization of a given performance index function and the philosophy of time-varying sliding mode control. Subsequently, a discontinuous control law is designed for guaranteeing the existence of the sliding mode throughout the entire response of the system. Therefore, the global robustness can be ensured. Simulation example is finally given to illustrate the effectiveness of the proposed controller.

关键词： Re-entry vehicle Attitude control SDRE Optimal time-varying sliding mode control

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Chaotic Particle Swarm Optimization Algorithm Parametric Identification of Bouc-Wen hysteresis Model for Piezoelectric Ceramic Actuator

Chaotic Particle Swarm Optimization Algorithm Parametric Ide...

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第25届中国控制与决策会议

作者： Ning Dong Hongjuan Li Xiangdong Liu Key Laboratory for Intelligent Control & Decision of Complex Systems Beijing Institute of Technology School of Automation Beijing Institute of Technology

ISBN: (纸本)9781467355339

A chaotic particle swarm optimization (CPSO) algorithm is proposed by introducing chaos state into the original Particle Swarm Optimization (PSO) which aims to solving the flaws of easy plunging into local optimum and losing search ability in the last period for the fast particle velocity decrease. CPSO algorithm takes advantage of the ergodicity, randomicity, and regularity of chaos to make chaotic searching for the global extremun at the same time with the particle swarm optimization. This algorithm synthesizes the high efficiency of global optimization of PSO algorithm and the ergodicity and randomicity of local search of chaotic algorithm. This paper utilizes aforementioned algorithm to identify the Bouc-Wen hysteresis model for piezoelectric ceramic actuators (PCA). The experimental results show that the model identified by CPSO algorithm has better performance than that by PSO algorithm.

关键词： Chaotic Particle Swarm Optimization Bouc-Wen Identification Piezoelectric Ceramic Actuator

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Observer-based fuzzy control for nonlinear fractional-order systems via fuzzy T-S models: The 1 < α < 2 case

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IFAC Proceedings Volumes 2014年第3期47卷 6086-6091页

作者： Zhe Gao Xiaozhong Liao College of Light Industry Liaoning University Shenyang 110036 P. R. China School of Automation Beijing Institute of Technology Beijing 100081 P. R. China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081 P. R. China

This paper presents observer-based fuzzy control for nonlinear fractional-order systems with the fractional order α satisfying 1 < α < 2 via fuzzy T-S models. Using the properties of the Kronecker product and LMI approach, the feedback and observer gain matrices are designed. By this method, the state of nonlinear system described as the fuzzy T-S model is convergent to the equilibrium and the observer error is convergent to zero. Finally, the simulation result of a numerical example is given to illustrate the effectiveness of this method.

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Multi-target Passive Location Based on the Algorithm of TDOA-Camberra

Multi-target Passive Location Based on the Algorithm of TDOA...

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第25届中国控制与决策会议

作者： Xin Xu Wenjie Chen Mingjun Jiang School of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision (Beijing Institute of Technology) Ministry of Education China North Vehicle Research Institute

ISBN: (纸本)9781467355339

An algorithm namely the TDOA-Camberra is proposed for the multi-target passive location in this paper. The algorithm uses the Camberra distance to associate the target data and do the optimal search, then uses the time difference of arrival (TDOA) to locate multiple targets passively once data from the same target is determined. At the same time, as the computing time of associating data using Camberra distance is long, the improved sequential similarity detection algorithm (SSDA) is added to the calculation in order to shorten the time of the data association, thus to increase the speed of the multi-target passive location. The theoretical analysis and simulation experiment proves that the multi-target passive location can be implemented by the proposed algorithm accurately and quickly.

关键词： passive location, data association, Camberra distance, SSDA

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Pyramid histogram of oriented gradient and particles swarm optimization based SVM for vehicle detection

Pyramid histogram of oriented gradient and particles swarm o...

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2013 7th International Conference on Image and Graphics, ICIG 2013

作者： Wang, Hailuo Bo, Wang Sun, Li College of Automation Beijing Institute of Technology Beijing China Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China

ISBN: (纸本)9780769550503

Vehicle Detection is an important part in intelligent transportation system (ITS) and driver assistance system. Considering vehicles have strong edges and lines in different orientation and scales, in this paper, we presents a method for detecting vehicles based on a feature named Pyramid Histogram of Oriented Gradient. This feature provides spatial distribution information of edges which was often ignored by other features. Specifically, we extract PHOG features from a traffic image and a vector is obtained as representation of this image. In order to speed up the process of calculation, Principle Component Analysis (PCA) algorithm is applied to these vectors to reduce their dimensionality. Tests show the efficiency improved significantly. Theses representative vectors are then used to train SVM classifier. To ensure the final classification accuracy, we adopt Particles Swarm Optimization (PSO) method to gain the parameters used in SVM classification. Optimal parameters correspond with optimal result. Experiments demonstrate the superiority of the proposed approach which has achieved an average accuracy of 95% on test images. © 2013 IEEE.

关键词： Vehicles

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Sensor Fault Detection with Online Sparse Least Squares Support Vector Machine

Sensor Fault Detection with Online Sparse Least Squares Supp...

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第三十二届中国控制会议

作者： Guo Su Deng Fang Sun Jian Li Fengmei School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex

ISBN: (纸本)9781479900305

In this paper,we present the theory of online sparse least squares support vector machine(OS-LSSVM) for prediction and propose a predictor with OS-LSSVM to detect sensor *** principle of the predictor and its online algorithm are *** with the traditional least squares support vector machine(LSSVM),OS-LSSVM has an advantage on training speed owing to the online training algorithm based on the base vector *** real-time output data of sensor is employed as the training vector to establish the regression *** method is compared with the LSSVM predictor in the *** typical faults of sensors are investigated and the simulation result indicates that the OS-LSSVM predictor can diagnose sensor fault accurately and rapidly,thus it is especially suitable for online sensor fault detection.

关键词： sensor fault detection OS-LSSVM LSSVM

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Decentralized Filtering a Multi-Agent system with Local Parametric Couplings Based On Kalman Filter

Decentralized Filtering a Multi-Agent System with Local Para...

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第25届中国控制与决策会议

作者： Yini Lv Hongbin Ma Mengyin Fu Chenguang Yang Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institution of Technology School of Computing and Mathematics Plymouth University

ISBN: (纸本)9781467355339

In this paper, decentralized filtering of multiagent systems with coupling uncertainties is proposed and investigated. The considered multi-agent system is composed of many agents, each of which evolves with a discrete-time stochastic linear time-varying dynamics, and every agent can be locally influenced by its neighbor agents. Therefore the states evolution of each agent is not only related with its previous states but also related with its neighbors' previous states in the linear dynamic system. Communication limitations existing in the considered multi-agent system restrict that each agent can only observe its own measurements (outputs) and its neighbor agents' outputs while the states are invisible to any agent. Because of communication limitations and information constraints, without knowing the coupling gains of the local interactions, it is not easy for each agent to estimate its states by traditional kalman filter or other state observers, which were extensively discussed in the literature. In this preliminary study, for the considered coupled linear discrete-time multiagent system with uncertain linear local couplings, based on the key idea of state augmentation and the certainty-equivalence principle borrowed from the area of adaptive control, we propose an efficient decentralized kalman filtering scheme, for each agent, to simultaneously estimate the unknown states and coupling parameters, and extensive simulations are conducted, which have clearly verified the effectiveness of the proposed decentralized filtering scheme.

关键词： multi-agent system, kalman filter, parametric couplings, parameter estimation, states estimation, decentralized filtering

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