检索结果-内蒙古大学图书馆

作者： Sun, Wei Bai, Yongqiang Jia, Rui Xiong, Rui Chen, Jie School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Ministry of Education Beijing 100081 China

ISBN: (纸本)9788995605646

The agents connected by networks are capable to reach a prescribed state if only a small fraction of them are controlled with feedback information. The present work tries to stabilize groups of non-linear agents in a directed network onto a stable state with several equilibriums. The agent dynamics can be identical or heterogeneous. But the agents in the same group share a same non-linear model. The conditions to reach multiple consensus states are provided under both non-switching and switching topologies. The maximum number of heterogeneous equilibriums is discussed. It is proved theoretically and by simulations that under certain conditions, pinning control can lead a multi-group network to reach a multi-valued consensus state. © 2011 Asian control Association.

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Recursive blind LMS parameter identification for single-input multiple-output system

Recursive blind LMS parameter identification for single-inpu...

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作者： Chen, Jie Ma, Tao Chen, Wenjie Zhang, Bo School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Ministry of Education Beijing 100081 China

ISBN: (纸本)9788995605646

A blind least-mean-squares (BLMS) algorithm is proposed for the parameter identification of single-input multiple-output (SIMO) systems. Without requiring knowledge of a reference signal, it is proved that the presented parameter estimates almost sure converge to their real value under the assumption that the observed noises are mutually independent distributed additive white sequence with known variance. The noise variance of observed signal is estimated from the eigenvalues of a matrix related to observed signal sequence firstly. We back our theoretical findings with experiments showcasing the potential merits of the BLMS in practice. © 2011 Asian control Association.

关键词： Eigenvalues and eigenfunctions

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Obstacle Avoidance for Kinematically Redundant Robot

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IFAC-PapersOnLine 2015年第28期48卷 490-495页

作者： WANG, Xinyu YANG, Chenguang CHEN, Junshen MA, Hongbin LIU, Feng School of Automation Beijing Institute of Technology Beijing China State Key Lab of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Centre for Robotics and Neural Systems Plymouth University Plymouth United Kingdom College of Automation Science and Engineering South China University of Technology Guangzhou China Beijing Jiaotong University Beijing China

Manipulator's obstacle avoidance is always a challenging topic in robotics. With the concern of the safety problems in human working environment, an improved obstacle avoidance method is proposed based on the general solution of the inverse kinematic problem of a redundant manipulator. A new obstacle detection method using Kinect R sensor is designed to give a robust obstacle information. By designing a parallel system of the manipulator, the proposed control method is not only to achieve the goal of moving away from the obstacle, but also able to guarantee the robot move back to its original pose. The stability of the closed-loop system is established using Lyapunov direct method to ensure the asymptotic stability of the system. The performance of the simulation results verifies the effectiveness of the proposed obstacle detection algorithm and the obstacle avoidance method. © 2015

关键词： Inverse problems Asymptotic stability Closed loop systems Collision avoidance Inverse kinematics Obstacle detectors Redundant manipulators system stability General solutions Inverse kinematic problems Kinematically Redundant Lyapunov direct method Obstacle detection Parallel system Redundant robot Working environment

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Sparse Least Square Support Vector Machines based on Random Entropy 36

Sparse Least Square Support Vector Machines based on Random ...

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第36届中国控制会议

作者： Wenlu Ma Han Liu Faculty of Automation and Information Engineering Xi'an University of Technology Shaanxi Key Lab. of Complex System Control and Intelligent Information Processing Faculty of Automation and Information EngineeringXi’an University of Technology

ISBN: (纸本)9781538629185

Least squares support vector machines(LSSVM) has a good performance in small data samples, but can't solve the large-scale sample problems. In this paper, large data set sparse least squares support vector machines model based on stochastic entropy is proposed, and it can be applied to large-scale data samples. Firstly, the large-scale data set is divided into several subsets. Then the entropy method is used to the sparse samples in each subset. Finally, we use sparse samples sets as training samples, and use least squares support vector machine algorithm to train. The results show that the sparse least squares support vector machine model based on entropy can effectively solve the problem of large-scale data.

关键词： Sparsity LSSVM Large-scale data Random Entropy

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New method of sparse visual saliency feature extraction and application in unmanned vehicle environment sensing

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Information Technology Journal 2013年第20期12卷 5914-5921页

作者： Du, Ming-Fang Wang, Jun-Zheng Li, Jing Cao, Hai-Qing Key Laboratory of Complex System Intelligent Control Decision Beijing Institute of Technology Ministry of Education 100081 Beijing China

A new method based on Hessian matrix threshold of finding local low-level saliency features is proposed in this study after the standard local invariant feature extraction algorithm SRUF (Speeded Up Robust Features) is analyzed. In this method, the number of saliency feature points can change with the change of Hessian threshold. The saliency feature points will become sparser when Hessian threshold becomes larger. When a certain extreme threshold which is defined as Hessian Threshold Node is reached, the retained discriminative feature points are remarkable stability characteristics, also make up the best sparse saliency features set. This method is applied in the unmanned vehicle environment sensing system to help extract the before going vehicle's saliency feature and realize object tracking and obstacle detection. Experiment results show that this is an quick and robust method to determine saliency feature points quantitatively and is very suitable for the occasion which has strong demand on real-time. © 2013 Asian Network for Scientific Information.

关键词： Object detection

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Optimal switching integrity attacks in cyber-physical systems

Optimal switching integrity attacks in cyber-physical system...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Guangyu Wu Jian Sun The Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China

ISBN: (纸本)9781538629024

In this paper, an optimal switching data integrity attack schedule method is presented. It is assumed that an attacker is able to inject false data to partial actuators of a healthy system at each instant. Optimal switching attack represents a growing class of cyber-physical attacks that aim to damage a target system via a controlled switching of attacked units. A feedback attack law is proposed to maximize a weighted quadratic performance. Two switching conditions are designed to obtain the optimal sequence of the attacked actuators via the Maximum Principle. Finally, numerical results are provided to illustrate the effectiveness of the proposed method.

关键词： Switches Actuators Cyber-physical systems Jamming Optimal control system performance

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Research on Path Planning of Mobile Robot Based on DWA-IMP-A∗ Algorithm 42

Research on Path Planning of Mobile Robot Based on DWA-IMP-A...

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42nd Chinese control Conference, CCC 2023

作者： Liu, Zhi Zhang, Lin Wang, Shoukun Niu, Tianwei Xu, Yongkang Cao, Jin School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China School of Automation Beijing Institute of Technology Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information Technology Beijing100081 China

ISBN: (纸本)9789887581543

Path planning is one of the most critical links in mobile robots. Its timeliness, security and accessibility are crucial to the development and wide application of mobile robots. However, in solving the problem of path planning, the most popular A∗ algorithm has some problems, such as heuristic function cannot be estimated accurately, node redundancy, path is not smooth, and obstacle avoidance cannot be achieved in real time. To solve these problems, A fusion algorithm of improved A∗ combined with reverse path and dynamic window method (DWA-IMP-A∗) was proposed. The algorithm refines the heuristic function by incorporating the reverse path. The node optimization algorithm is used to further reduce the path length. The generated trajectories are smoothed by cubic spline interpolation. At the same time, it is integrated with the improved DWA algorithm to improve the efficiency and safety of robot path planning. The algorithm takes ROS mobile robot as the carrier and is tested under typical road conditions. Compared with A∗ algorithm, the planning time is reduced by 54.6% and the path length is reduced by 6.37%. Experimental results verify the effectiveness and robustness of the algorithm. The research results have certain reference significance for the path planning of various types of mobile robots and the research of driverless vehicles. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Motion planning

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Nonuniformity Correction and Calibration Method in the High-precision CCD Measurement and Servo control system

Nonuniformity Correction and Calibration Method in the High-...

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Joint 48th IEEE Conference on decision and control and 28th Chinese control Conference

作者： Jing LI Junzheng WANG Bin ZHOU Wei SHEN Key Laboratory of Complex System Intelligent Control and Decision School of AutomationBeijing Institute of Technology

The CCD pixels nonuniformity may give a greater margin of error to measurement results in the high-precision CCD measurement and servo control *** paper analyzes the image pixels nonuniformity caused by noises,and establishes the corresponding image *** threshold value segmentation algorithm is used for image *** algorithm using two point linear method for pixel nonuniformity correction,getting center coordinates of facula by calculating the zeroth order moment and first moment of image is put forward,and a new image calibrated method that transforms the image coordinates into the real is *** results show that the algorithm can separate light intensity parts from the image,correct pixel nonuniformity,and stabilize pixel gray value of light intensity *** will make the center coordinates of image light intensity spots stable and decrease the error of the real coordinates after conversion,if the images are acquired under the same *** measurement precision as well as the control precision is improved greatly.

关键词： image Nonuniformity Correction and Calibration Method in the High-precision CCD Measurement and Servo control system CCD

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Fault-tolerant sampled-data synchronization of Markovian jumping complex dynamical networks via looped-functional approach

Fault-tolerant sampled-data synchronization of Markovian jum...

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International Symposium on Autonomous systems (ISAS)

作者： Wang Xin Sun Jian Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China

ISBN: (纸本)9781728112992

In this paper, the issue of sampled-data synchronization of Markovian jumping complex dynamical networks with sensor fault is investigated. Here, we utilize looped-functional approach to constructed Lyapunov functional with more information about r(t k ) and r(t k+1 ), which has contribution to decrease the conservatism of stability condition. Then, we design a sampled-data controller for Markovian jumping complex dynamical networks. Finally, the feasibility and superiority of our method are proved by several numerical and simulation examples.

关键词： complex networks control system synthesis fault tolerant control Lyapunov methods Markov processes network theory (graphs) sampled data systems stability synchronisation sampled data system fault-tolerant control control system synthesis Lyapunov methods Markov chain complex networks data synchronization Jumping Data sampling

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Single image haze removal algorithm using pixel-based airlight constraints

Single image haze removal algorithm using pixel-based airlig...

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International Conference on Automation and Computing (ICAC)

作者： Zhenwei Gao Yongqiang Bai Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China

Fast single image dehazing has been a challenging problem in many fields, such as computer vision and real-time applications. The existing image dehazing algorithms cannot achieve a trade-off between the dehazing performance and the computational complexity. The proposed approach first applies the mean filter twice to estimate airlight, which include pixel-based dark channel and bright channel constraints. And then the relationship between channel values of the restored image and atmospheric light is qualitatively analyzed to give the optimum estimate of atmospheric light. Using the airlight and atmospheric light, we can easily restore the scene radiance via the atmospheric scattering model. Compared with others, the main advantage of the proposed approach is its high speed and significant visibility improvement even in the sky and white areas. This speed allows the enhanced haze image to be applied in real-time processing applications. A comparative study and quantitative evaluation are proposed with a few other state of the art algorithms which demonstrates that similar or better quality results are obtained.

关键词： Atmospheric modeling Image restoration Real-time systems Channel estimation Scattering Filtering Computational modeling

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