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Two-stage ARMAX parameter identification based on bias-eliminated least squares estimation and Durban's method

Zidonghua Xuebao/Acta Automatica Sinica 2012年第3期38卷 491-496页

作者： Xin, Bin Bai, Yong-Qiang Chen, Jie School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing 100081 China Decision and Cognitive Sciences Research Centre Manchester Business School The University of Manchester Manchester M15 6PB United Kingdom

This paper proposes a two-stage identification approach for the parameter identification of autoregressive moving average with exogenous variable (ARMAX) model. First, a bias-eliminated least squares method is employed to identify the autoregressive part with exogenous variable (ARX). Then, the Durbin's method is employed to transform the parameter identification of the moving average (MA) part into that of a long autoregressive (AR) model. The MA parameters are derived directly from the parameter relationship between the MA part and its equivalent long AR model. Finally, the noise variance can be computed by using the identified MA parameters. The performance comparison against the extended least-squares method in numerical simulations validates the effectiveness of the two-stage identification approach. Copyright © 2012 Acta Automatica Sinica. All rights reserved.

关键词： Parameter estimation

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A weighted pattern recognition algorithm for short-term traffic flow forecasting

A weighted pattern recognition algorithm for short-term traf...

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IEEE International Conference on Networking, Sensing and control

作者： Shuangshuang Li Zhen Shen Fei-Yue Wang State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center for Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

The k-nearest neighbor (k-NN) nonparametric regression is a classic model for single point short-term traffic flow forecasting. The traffic flows of the same clock time of the days are viewed as neighbors to each other, and the neighbors with the most similar values are regarded as nearest neighbors and are used for the prediction. In this method, only the information of the neighbors is considered. However, it is observed that the “trends” in the traffic flows are useful for the prediction. Taking a sequence of consecutive time periods and viewing the a sequence of “increasing”, “equal” or “decreasing” of the traffic flows of two consecutive periods as a pattern, it is observed that the patterns can be used for prediction, despite the patterns are not from the same clock time period of the days. Based on this observation, a pattern recognition algorithm is proposed. Moreover, empirically, we find that the patterns from different clock time of the days can have different contributions to the prediction. For example, if both to predict the traffic flow in the morning, the pattern from the morning can lead to better prediction than same patterns from afternoon or evening. In one sentence, we argue that both the pattern and the clock time of the pattern contain useful information for the prediction and we propose the weighted pattern recognition algorithm (WPRA). We give different weights to the same patterns of different clock time for the prediction. In this way, we take both virtues of the k-NN method and the PRA method. We use the root mean square error (RMSE) between the actual traffic flows and the predicted traffic flows as the measurement. By applying the results to actual data and the simulated data, about 20% improvement compare with the PRA is obtained.

关键词： Clocks Data models Pattern recognition Prediction algorithms Mathematical model Meteorology Vectors

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A novel parking control algorithm for a car-like mobile robot

A novel parking control algorithm for a car-like mobile robo...

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IEEE International Conference on Networking, Sensing and control

作者： Yaru Zhang Shuming Tang Zhilin Zhang State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

This paper proposes a novel algorithm for parking motion of a Car-like mobile robot. The algorithm presented here addresses calculating equations for planning a parking path in real time. Moreover, by incorporating the constraints of the mechanical and kinematical characteristics of the car and the geometry of the parking lot in the path planning, we can turn a parking problem into solving algebraic equations. By tracking a planned path, the Car-like mobile robot can drive into the parking area without hitting any boundaries. The efficiency of the proposed algorithm is demonstrated by simulation.

关键词： Vehicles Mobile robots Algorithm design and analysis Mathematical model Turning Equations Signal processing algorithms

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A review on vision-based pedestrian detection in intelligent transportation systems

A review on vision-based pedestrian detection in intelligent...

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IEEE International Conference on Networking, Sensing and control

作者： Bo Li Qingming Yao Kunfeng Wang State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

Pedestrians are key participants in transportation systems, so pedestrian detection in video surveillance systems is of great significance to the research and application of intelligent Transportation systems (ITS). We review some methods and models for vision-based pedestrian detection in recent years. In this paper, the pedestrian detection techniques are divided into macroscopic and microscopic according to different application in transportation systems. Macroscopic pedestrian detection aims to estimate crowd density without distinguishing each pedestrian, and microscopic pedestrian detection focuses on detection and recognition of individual pedestrians. The latter detection style is deeply studied, so it is presented in detail in this paper, especially for the feature-classifier-based detection method. Finally, the pedestrian detection algorithms are discussed and concluded from the viewpoint of video surveillance and ITS. Existing problems and future trends are presented in that section.

关键词： Feature extraction Shape Training Transportation Traffic control Video surveillance

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A vehicle license plate recognition system based on analysis of maximally stable extremal regions

A vehicle license plate recognition system based on analysis...

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IEEE International Conference on Networking, Sensing and control

作者： Bo Li Bin Tian Qingming Yao Kunfeng Wang State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

Vehicle License Plate Recognition (VLPR) system is a core module in intelligent Transportation systems (ITS). In this paper, a VLPR system is proposed. Considering that license plate localization is the most important and difficult part in VLPR system, we present an effective license plate localization method based on analysis of Maximally Stable Extremal Region (MSER) features. Firstly, MSER detector is utilized to extract candidate character regions. Secondly, the exact locations of license plates are inferred according to the arrangement of characters in standard license plates. The advantage of this license plate localization method is that less assumption of environmental illumination, weather and other conditions is made. After license plate localization, we continue to recognize the license plate characters and color to complete the whole VLPR system. Finally, the proposed VLPR system is tested on our own collected dataset. The experimental results show the availability and effectiveness of our VLPR system in locating and recognizing all the explicit license plates in an image.

关键词： Licenses Image color analysis Character recognition Lighting Histograms Feature extraction Image segmentation

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Rear lamp based vehicle detection and tracking for complex traffic conditions

Rear lamp based vehicle detection and tracking for complex t...

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IEEE International Conference on Networking, Sensing and control

作者： Ye Li Qingming Yao State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

In video surveillance system, detection and tracking of vehicles are two foundational and significant tasks. In this paper, a vehicle detection and tracking method based on rear lamp pairs is proposed. The proposed method combines color with motion information to perform vehicle detection. In order to adapt to different weather conditions like night, the rear lamps are divided into two categories: unlit lamps and lighted lamps. First, threshold segmentation are used to extract both the unlit and lighted lamp candidates in hue-saturation-value (HSV) color space and the thresholds are selected automatically by maximally stable extremal region (MSER) method. Then, all lamp candidates are tracked by using Kalman filter and lamp candidates with short-lived trajectories are removed to avoid disturbances. Next, two adjacent lamp candidates with similar speed are bound together as a region of interest (ROI), which represents a potential pair of lamps. Image cross-correlation symmetry analysis based on Gabor filter is utilized to find the ROIs with symmetrical texture and these symmetric ROIs can be regarded as pairs of lamps. The experimental results show that the proposed method can effectively deal with various illumination conditions and improve the accuracy and robustness of vehicle detection. In addition, this method can perform vehicle detection and tracking under complex traffic conditions and the Gabor filter based symmetry analysis can successfully suppress subtle difference between the left and right parts of a vehicle as well as environment noises.

关键词： Vehicles Image color analysis Vehicle detection Gabor filters Correlation Tracking Kalman filters

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Stability Analysis for High Frequency Networked control systems

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IEEE Transactions on Automatic control 2012年第10期57卷 2694-2700页

作者： Hongjiu Yang Yuanqing Xia Peng Shi Mengyin Fu Institute of Electrical Engineering Yanshan University Qinhuangdao China School of Automation Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China School of Engineering and Science Victoria University Melbourne VIC Australia Department of Computing and Mathematical Sciences University of Glamorgan Pontypridd UK

This note generalizes the stability analysis for a high frequency networked control system. The high-frequency networked control system is described by a delta operator system with a high frequency constraint. Stability conditions are given for the high frequency delta operator system. Furthermore, by developing the generalized Kalman-Yakubovic-Popov lemma, improved stability conditions are also presented in terms of linear matrix inequalities. Some experiment results are presented to illustrate the effectiveness of the developed techniques.

关键词： Stability analysis Delay Linear matrix inequalities Frequency control Educational institutions Power system stability Numerical stability

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New stability criteria for linear systems with time-varying interval delay

New stability criteria for linear systems with time-varying ...

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UKACC International Conference on control (control)

作者： Jian Sun Jie Chen G.P. Liu School of Automation Key Laboratory of Complex Systems Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing China CTGT Center Harbin Institute of Technology Harbin China Faculty of Advanced Technology University of Glamorgan Pontypridd UK

This paper is concerned with the problem of stability of systems with time-varying delay in a given interval. A novel Lyapunov-Krasovskii functional is proposed to obtain new stability conditions. Some triple integral terms are introduced in the Lyapunov-Krasovskii functional and the information on the lower bound on the delay are sufficiently used. New delay-dependent stability criteria are derived using integral inequalities and formulated in terms of linear matrix inequality (LMI). Comparing numerical examples show that the proposed criteria yield a larger upper bound on the delay for a given lower bound on the delay than existing results.

关键词： Delay Stability criteria Time varying systems Linear matrix inequalities Numerical stability Linear systems

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A Two-stage ARMAX Identification Approach Based on Bias-eliminated Least Squares and Parameter Relationship between MA Process and Its Inverse

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Acta Automatica Sinica 2012年第3期38卷 491-496页

作者： Bin XIN Jie CHEN School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing 100081 China Decision and Cognitive Sciences Research Centre Manchester Business School University of Manchester M15 6PB Manchester UK

In this paper, a two-stage approach is proposed for the parameter identification of autoregressive moving average with exogenous (ARMAX) variable model. The proposed approach identifies the autoregressive part with exogenous variable (ARX) by a bias-eliminated least squares method, and the moving average (MA) part by utilizing the parameter relationship between MA process and its inverse. Finally, the noise variance can be computed by using the identified MA parameters. Numerical simulations validate the effectiveness of the proposed approach.

关键词： Autoregressive moving average with exogenous (ARMAX) model parameter identification inverse model least-squares method bias compensation

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Consensus control of linear multi-agent systems with distributed adaptive protocols

Consensus control of linear multi-agent systems with distrib...

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American control Conference (ACC)

作者： Zhongkui Li Xiangdong Liu Wei Ren Lihua Xie Key laboratory for Intelligent Control & Decision of Complex Systems Beijing Institute of Technology Beijing P. R. China Department of Electrical Engineering University of California Riverside CA USA School of Electrical and Electronic Engineering Nanyang Technological University Singapore

ISBN: (纸本)9781457710957

This paper considers the distributed consensus problem of multi-agent systems with general continuous-time linear time-invariant dynamics. Based on the relative output information of neighboring agents, two distributed adaptive dynamic consensus protocols are proposed, namely, the edge-based adaptive protocol which assigns a time-varying coupling weight to each edge in the communication graph and the node-based adaptive protocol which uses a time-varying coupling weight for each node. These two adaptive protocols are designed to ensure that consensus is reached in a fully distributed fashion for any undirected connected communication graphs without using any global information. A sufficient condition for the existence of these adaptive protocols is that each agent is stabilizable and detectable. The case with switching communication graphs is also studied.

关键词： Protocols Eigenvalues and eigenfunctions Couplings Switches Linear matrix inequalities Laplace equations Lyapunov methods

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