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Chinese control Conference (CCC)

作者： Jing Li Junzheng Wang Jiali Mao Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Beijing Beijing CN

Moving object detection is usually used in gray image, and the color image should be converted to gray images to achieve detection. However, the color object can't be described by simple gray information completely. In order to achieve automatic color moving object detection, the method based on automatic color clustering is especially proposed. Because the difference between adjacent pixels in an image is very small, the initial cluster center can be moved in the maximum distance. The proposed method can reduce the number of iterations and quicken convergence speed, meanwhile determine the number of color cluster and the location of the color object automatically. The proposed algorithm is validated in the actual system, experimental results show that the proposed method can automatically achieve color clustering for color image, while detect color objects.

关键词： Image color analysis Clustering algorithms Image segmentation Color Classification algorithms Object segmentation Object detection

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Sequential Fusion and State Estimation for Asynchronous Multirate Multisensor Dynamic systems

Sequential Fusion and State Estimation for Asynchronous Mult...

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第三十三届中国控制会议

作者： Lu Jiang Liping Yan Bo Xiao Yuanqing Xia Mengyin Fu School of Automation Key Laboratory of Intelligent Control and Decision of Complex SystemsBeijing Institute of Technology School of Information and Communication Engineering Beijing University of Posts and Telecommunications

A sequential fusion and state estimation algorithm for an asynchronous multirate multisensor dynamic system is presented in this *** dynamic system at the finest scale is *** are multiple sensors observing a single target independently with different sampling rates,and the observations are obtained *** present algorithm is shown to be more effective and efficient than the existed *** on a radar tracking system with three sensors are done and show the effectiveness of the present algorithm.

关键词： state estimation,sequential fusion,asynchronous,multirate multisensor,Kalman filter

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The Fusion of Multisensor Images with Multi-resolutions

The Fusion of Multisensor Images with Multi-resolutions

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第三十三届中国控制会议

作者： Liping Yan Bo Xiao Yuanqing Xia Meiling Wang Mengyin Fu School of Automation Key Laboratory of Intelligent Control and Decision of Complex SystemsBeijing Institute of Technology School of Information and Communication Engineering Beijing University of Posts and Telecommunications

ISBN: (纸本)9781479947249

Images taken by different sensors at different time instant with different resolutions are formulated by state space models, and are fused by use of Multiscale Kalman Filter(MKF). The effectiveness of the presented algorithm is shown by comparing it with the wavelet based method through experiments, where four performance measures are used. The performance evaluation indices are the root mean square errors(RMSE), the information entropy(Entropy), the space frequency(SF) and the space visibility(SV). Theretical analysis and experimental results show the effectiveness of the presented algorithm.

关键词： Image fusion,multiresolution,multiscale Kalman filter,state space model

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Modeling of hysteresis in piezoelectric actuator based on adaptive IIR filter

Modeling of hysteresis in piezoelectric actuator based on ad...

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IEEE International Conference on Mechatronics and automation

作者： Ning Dong Fengmin Shan Xiangdong Liu Key Laboratory for Intelligent Control & Decision of Complex Systems Beijing Institute of Technology Beijing China

This paper presents a novel adaptive IIR filter modeling for the hysteresis characteristic in PEA (piezoelectric actuator). First, the PEA hysteresis operators are introduced and the modeling methods of traditional adaptive IIR (infinite-impulse response) filter are discussed. Then, delay operators of IIR adaptive filter are replaced with Backlash operators to compose a new adaptive IIR filter model. During the modeling process, LMS (Least Mean Square) algorithm is used to adjust the weight values. At last the modeling effectiveness is verified via a micro-positioning system experiment platform based on PEA. Experimental results show that the proposed Backlash operator based IIR adaptive filter can achieve accurate hysteresis modeling.

关键词： Adaptation models IIR filters Finite impulse response filters Adaptive filters Mathematical model Hysteresis Delays

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Improved ICCP algorithm and its application in gravity matching aided inertial navigation system

Improved ICCP algorithm and its application in gravity match...

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Chinese control Conference (CCC)

作者： Meiqi Liu Bo Wang Zhihong Deng Mengyin Fu School of Automation and National Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing Beijing CN

Considering two disadvantages in traditional gravity matching aided inertial navigation system, low matching accuracy and error accumulation, we propose an improved gravity matching algorithm and aided method for inertial navigation system. Instead of using the sequence sampling, the single point sampling is applied to improve the structure of proposed algorithm, enhancing the matching speed and efficiency. In the aided navigation system method, we use combination of Sage-Husa adaptive filter and strong-tracked Kalman filter to make further optimal estimation of the matching trajectory. Simulation results show the effectiveness of the real-time ICCP algorithm and the combined filter algorithm. Comparing to the traditional methods, proposed method provides higher matching and navigation accuracy.

关键词： Gravity Filtering algorithms Algorithm design and analysis Navigation Accuracy Filtering theory

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Distributed adaptive tracking on Lagrangian systems with reduced interaction

Distributed adaptive tracking on Lagrangian systems with red...

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World Congress on intelligent control and automation (WCICA)

作者： Yuchen Liu Hao Fang Yutian Mao Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

In this paper, we propose a distributed adaptive approach for tracking problem without using leader's velocity information, where agents are modeled by Euler-Lagrange equations. It is assumed that only a small fraction of agents within the leader's communication range are informed about the position of the leader. Without using the leader's velocity information, a connectivity-preserving adaptive controller is proposed to achieve tracking control on Lagrangian systems with the leader of constant velocity. Moreover, position and velocity consensus can be achieved asymptotically with the proposed control strategy. Numerical simulations are further provided to illustrate the theoretical results.

关键词： intelligent control automation

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complex Terrain Perception based on Hidden Markov Model

Complex Terrain Perception based on Hidden Markov Model

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IEEE International Conference on intelligent Transportation systems

作者： Meiling WANG Liang ZUO Yi YANG Qiangrong YANG Tong LIU School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Intelligent Control and Decision of Complex System Beijing China

Terrain perception in complex environment is important for Autonomous Land Vehicle to drive automatically. In order to access the terrain information, in this paper, we present a terrain perception method based on Hidden Markov Model (HMM) which combines LIDAR with machine vision. On the basis of spatial fan-shaped model, terrain feature extraction is performed to acquire the observation model. Hidden markov models describe the vertical structure of the driving space and Viterbi algorithm is used for terrain classification. Then the navigation decision is given based on the perception of the complex environment. Experiment results show that the method can give an accurate environment description for ALV.

关键词： terrain perception sensor fusion feature extraction principal component analysis multihidden markov models

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An Approach of Bayesian Filtering for Stochastic Boolean Dynamic systems

An Approach of Bayesian Filtering for Stochastic Boolean Dyn...

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第26届中国控制与决策会议

作者： Hongbin MA Dong WANG Hongsheng QI Mengyin FU School of Automation Beijing Institute of Technology the State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology the Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of Sciences

This paper introduces an approach to estimate the true states for stochastic Boolean dynamic system(SBDS), where the state evolution is governed by Boolean functions with additive binary process noise while the measurement is an arbitrary function of the state yet with additive binary measurement *** problem of figuring out the true state using the only available noisy outputs is crucial for practical applications of Boolean dynamic system models, however, for such Boolean systems with wide background, there are no ready-to-use convenient tools like Kalman filter for linear systems. To resolve this challenging problem, an approach based on Bayesian filtering called Boolean Bayesian Filter(BBF) is put forward to estimate the true states of SBDS, and an efficient algorithm is presented for their exact computation. An index to evaluate the filtering performance,named estimation error rate, is put forward in this paper as well. In addition, extensive simulations via actual examples have illustrated the effectiveness of the proposed algorithm based on BBF.

关键词： Stochastic Boolean dynamic systems,Bayesian filtering,estimation algorithm,estimation error rate

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Hybrid optimization of dynamic deployment for networked fire control system

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Journal of systems Engineering and Electronics 2013年第6期24卷 954-961页

作者： Chen Chen Jie Chen Bin Xin School of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education

With applying the information technology to the military field, the advantages and importance of the networked combat are more and more obvious. In order to make full use of limited battlefield resources and maximally destroy enemy targets from arbitrary angle in a limited time, the research on firepower nodes dynamic deployment becomes a key problem of command and control. Considering a variety of tactical indexes and actual constraints in air defense, a mathematical model is formulated to minimize the enemy target penetration probability. Based on characteristics of the mathematical model and demands of the deployment problems, an assistance-based algorithm is put forward which combines the artificial potential field （APF） method with a memetic algorithm. The APF method is employed to solve the constraint handling problem and generate feasible solutions. The constrained optimization problem transforms into an optimization problem of APF parameters adjustment, and the dimension of the problem is reduced greatly. The dynamic deployment is accomplished by generation and refinement of feasible solutions. The simulation results show that the proposed algorithm is effective and feasible in dynamic situation.

关键词： deployment optimization artificial potential field （APF） constraint handling generation of feasible solutions memetic algorithm

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Global Bounded Consensus of General Nonidentical Networks With Distributed Time-Delays

Global Bounded Consensus of General Nonidentical Networks Wi...

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IEEE Annual Conference on decision and control

作者： Xiuxian Li Housheng Su Chanying Li Zheng Wang Michael Z. Q. Chen Department of Mechanical Engineering The University of Hong Kong Pokfulam Hong Kong School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 PR China National Center for Mathematics and Interdisciplinary Sciences Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781479978878

In this paper, global bounded consensus problem of general nonidentical networks with nonlinear dynamics and distributed time-delays is investigated, in which the distributed time-delays are distinct from each other. The global consensus exists in the sense of boundedness since complete consensus does not often exist in the nonidentical case. With the aid of constructing a Lyapunov-Krasovskii functional and utilizing the technique of integral partitioning, some sufficient delay-dependent conditions are derived to ensure that global bounded consensus is achieved ultimately. Finally, effectiveness of the theoretical result is illustrated by a numerical example.

关键词： Bounded Nonlinear Dynamics numerical example Distribute Automatic incident detection Distinct

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