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第35届中国控制会议

作者： Luyu Li Zhen Li Xiangdong Liu Yongzhi Sheng School of Automation Beijing Institute of Technology Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781509009107

This paper addresses the stochastic stability problem of a modified extended Kalman filter(MEKF), targeted at the state estimation of the nonlinear system through wireless channel, where both transmission failure and channel fading are practically under consideration. For a class of nonlinear systems whose observation's Jacobi Matrix is always invertible, the sufficient conditions of the error covariance matrices are accordingly established. Moreover, the conditions for the stochastic stability of the estimation error are also derived, which is tighter than the conditions of boundedness of the error ***, a numerical example is given to demonstrate the feasibility of the proposed method.

关键词： Extended Kalman filter stochastic stability transmission failure fading

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H∞ Polytopic Filter Design for Nonlinear systems

H∞ Polytopic Filter Design for Nonlinear Systems

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第35届中国控制会议

作者： Yin Yu Zhen Li Jian Li Luyu Li Xiangdong Liu School of Automation Beijing Institute of Technology Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology

This paper proposes an H polytopic lter design for a nonlinear system. Based on the polytopic approximation of the nonlinear system, the polytopic lter design is converted into a group of linear matrix inequalities（LMIs） so that the polytopic lter parameters can be effectively acquired by numerical convex optimization algorithms. At this stage, the tensor product（TP） model transformation is utilized to compute the polytopic approximation of the nonlinear system. Particularly, a new recti cation procedure is further developed to obtain a specific polytopic approximation with all the vertex systems being stable, which premises the solvability of the LMIs. The method is much easier to be implemented than traditional approaches such as the Hamilton-Jacobi inequality（HJI）-based methods. Simulation demonstrates the method is much less conservative than the existing method and has good estimation performance.

关键词： H_∞ lter nonlinear systems polytopic model tensor product model transformation

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Framework of future innovative urban transport 19

Framework of future innovative urban transport

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19th IEEE International Conference on intelligent Transportation systems, ITSC 2016

作者： Dong, Xisong Zhou, Jiehan Hu, Bin Riekki, Jukka Xiong, Gang Wang, Feiyue Zhu, Fenghua State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China Center for Ubiquitous Computing University of Oulu Oulu Finland State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Cloud Computing Center Chinese Academy of Sciences Dongguan China Qingdao Academy of Intelligent Industries Qingdao China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781509018895

Rapidly growing urbanization is putting more pressure on the well-being of citizens and the environment. Applying the latest ICT technology to address urban transport challenges is a key strategy to release the new innovation powerhouse of urbanization. This paper introduces a framework of future Innovative Urban Transport (IUT), to support next generation urban transport, based on IoT, 4G, Big Data, Cloud Computing and other novel ICT technologies. We present the construction of the framework, its reference architecture, and contribution to the environmental and socially important impacts. IUT aims to advance the existing smart city transport, to foster urban innovations that maximize the well-being of citizens while minimizing the negative effects like traffic congestion, air pollution high resource congestion, and traffic accidents. © 2016 IEEE.

关键词： Traffic congestion

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Application of fuzzy cognitive map in information intelligent push

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Journal of Beijing Institute of Technology 2015年第4期24卷 553-557页

作者：张佳徐胜利邓方 School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems

Since computer system functions are becoming increasingly complex, the user has to spend much more time on the process of seeking information, instead of utilizing the required infor- mation. Information intelligent push technology could replace the traditional method to speed up the information retrieval process. The fuzzy cognitive map has strong knowledge representation ability and reasoning capability. Information intelligent push with the basis on fuzzy cognitive map could ab- stract the computer user＇ s operations to a fuzzy cognitive map, and infer the user＇ s operating inten- tions. The reasoning results will be translated into operational events, and drive the computer system to push appropriate information to the user.

关键词： fuzzy cognitive map artificial intelligence information intelligent push

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Analysis of underwater locomotion and improvement of FroBot

Analysis of underwater locomotion and improvement of FroBot

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2016 IEEE International Conference on Advanced intelligent Mechatronics, AIM 2016

作者： Yi, Yang Jianqing, Zhang Han, Xu Maokuan, Chen Lu, Zhang Zhongjing, Zhu School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Department of Electronic Engineering School of Information Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9781509020652

The main characteristic of FroBot is the dual-swing-legs propulsion mechanism, and it is necessary for us to conduct a series of experiments to study its propulsion model, both on land and underwater. As the propulsion of FroBot comes from the interaction force between caudal fins and water when it locomotes underwater, this paper presents an analysis about the propulsion and control of angle Θ. Then a number of underwater hydrodynamic simulations and analysis are also conducted to get a better control in reality. Finally, on the basis of propulsion model and experiments, we present the latest mechanical structure designs and further improvements to eliminate the limitations exposed in the previous generations of FroBot. © 2016 IEEE.

关键词： Propulsion

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Learning to Win in Evolutionary Two-person Boolean Game with Fixed Strategy Updating Rule

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IFAC-PapersOnLine 2015年第28期48卷 520-525页

作者： WANG, Dong Hongbin, M.A. Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institution of Technology Canada

This paper introduces an algorithm to learn the strategy updating rule for a two- person Boolean game using the records of the history strategies and game results. The two-person game in this paper is introduced as a zero-sum game along with a Boolean strategy set, and the strategies are governed by fixed Boolean functions whose arguments are the history strategies and game results with additive binary noise, which can be modeled as a stochastic Boolean dynamic system. However, for this easy-to-play game, there is no effective convenient methods to win more often. To achieve this goal, a learning algorithm based on Boolean regression and maximum-likelihood estimation is put forward to learn the strategy updating rule and the noise property using the records of the history strategies and game results. In addition, extensive simulations via actual examples have illustrated the effectiveness of the proposed learning algorithm. © 2015

关键词： Learning algorithms Identification (control systems) Maximum likelihood estimation Parameter estimation Stochastic systems Boolean dynamics Boolean games Extensive simulations Fixed strategy Learning Noise properties Strategy updating Two person game

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Identification for Switched systems

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IFAC-PapersOnLine 2015年第28期48卷 514-519页

作者： Hu, Qiong Fei, Qing Ma, Hongbin Wu, Qinghe Geng, Qingbo State Key Lab of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

For a class of unstable discrete-time multi-variable switched systems with parametric uncertainty, an identification scheme is developed in this paper. Specifically, the identification algorithm is derived to identify the parameter vectors of potential subsystems based on the idea of least geometric mean squares. Furthermore, an neural network classifier is put forward for partition of the identified subsystems. Finally, feasibility and effectiveness of the proposed identification scheme are verified by numerical simulations, which show that the desirable identification performance is guaranteed with the proposed scheme. © 2015

关键词： Parameter estimation Computational fluid dynamics Geometric mean Identification algorithms Identification scheme Multi variables Neural network classifier Parameter vectors Parametric uncertainties Switched system

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Optimal FPGA Implementation of High Speed Scale Space Generator 34

Optimal FPGA Implementation of High Speed Scale Space Genera...

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第三十四届中国控制会议

作者： LI Nan WANG Junzheng Key laboratory of intelligent control and decision of complex systems Beijing Institute of Technology

ISBN: (纸本)9781467374439

Scale space generation is a fundamental problem in almost all feature extraction algorithms. Often, it is a critical prior step of most image/video analytic applications that are based on the invariance or co-invariance of local features, such as SIFT based recognition, matching, and tracking applications. However, it is still quite a challenging problem to enable real-time applications of the extraction of local features due to the fact that scale space generation has a rather large computational complexity. This paper proposes the optimal FPGA design for acceleration of scale space generation. First, in order to derive the mathematical model for scale space generation that fits best in with the FPGA, we have discarded the conventional template convolution based Gaussian filtering scheme and adopted a novel IIR filter based recursive Gaussian blurring algorithm. Then, an approach based on the Retiming technique, which could find the minimal operational period for any given IIR filter, is used to finalize the overall design. For 1024×768 video, the proposed design is able to generate scale spaces at almost 400 fps, which is fast enough to support most real-time applications like object recognition, object matching, and 3D reconstruction.

关键词： Feature Extraction,Scale Space Generation,Recursive Gaussian Blurring,Retiming,FPGA Implementation

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The Application of Square-Root Cubature Kalman Filter in the SINS/CNS integrated navigation system

The Application of Square-Root Cubature Kalman Filter in the...

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2016 IEEE Chinese Guidance, Navigation and control Conference (IEEE CGNCC2016)

作者： Dongyang Zhang Zhihong Deng Bo Wang Mengyin Fu School of Automation and National Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Nanjing University of Science and Technology

ISBN: (纸本)9781467383196

The integrated navigation system can improve the navigation accuracy utilizing the redundant *** Extended Kalman Filter(EKF) is commonly used in the integrated navigation *** usually takes only one-order of Taylor expansion and needs to calculate the Jacobian matrix,which will affect the accuracy and numerical stability of the system *** in this paper the application of Square-Root Cubature Kalman Filter(SCKF) method was proposed to solve the above problems in the SINS/CNS integrated navigation *** simulation results show that the position,velocity and attitude errors are reduced effectively compared with the EKF *** SCKF method is more suitable for the state estimation problems in integrated navigation system.

关键词： The Application of Square-Root Cubature Kalman Filter in the SINS/CNS integrated navigation system Kalman CNS Filter

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Cooperative navigation for multiple autonomous underwater vehicles with time delayed measurements

Cooperative navigation for multiple autonomous underwater ve...

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2016 IEEE Chinese Guidance, Navigation and control Conference (IEEE CGNCC2016)

作者： Yuantao Qi Bo Wang Shunting Wang Mengyin Fu School of Automation and National Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Nanjing University of Science and Technology

ISBN: (纸本)9781467383196

Dealing with time delayed measurements is a key problem of cooperative navigation for multiple autonomous underwater vehicles(MAUVs).In this work,in order to solve the invalidation of location due to the time delayed measurements,an algorithm which based on the augmented extended Kalman filter(AEKF) is *** algorithm expands the variable dimension of slave AUV according to the time delayed measurements,and infers the fundamental equations of *** to the traditional EKF method,simulation results prove that AEKF has higher positioning accuracy.

关键词： AUV EKF Cooperative navigation for multiple autonomous underwater vehicles with time delayed measurements

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