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2.16 IEEE International Conference on Information and Automation, IEEE ICIA 2.16

作者： Meiling, Wang Zhen, Wang Yi, Yang Mengyin, Fu Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9781509041022

In this paper, a simplified dynamic vehicle model is established to accurately describe the dynamics of Unmanned Ground Vehicle (UGV) in trajectory tracking, while meeting the real-Time computing requirement. And a modified model predictive control (MPC) algorithm with soft constraint for UGV trajectory tracking is proposed to improve the tracking stability and rapidity. The optimal control problem at each sampling time is converted into a quadratic program (QP), which has mature solutions. To verify the trajectory tracking capabilities, the proposed MPC controller is compared with a PD controller under different longitudinal velocities. The simulation results demonstrate that the MPC controller can effectively reduce the tracking error and ensure the vehicle's traveling smoothness. © 2.16 IEEE.

关键词： Model predictive control

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Identification of interval models for a class of uncertain systems via linear programming

Identification of interval models for a class of uncertain s...

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作者： Zhang, Guozhu Chen, Jie Li, Zhiping Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology School of Automation Beijing 100081 China

ISBN: (纸本)9781424474264

The interval models of uncertain plants are frequently used in the field of robust control. In this paper, a novel interval model identification method based on linear programming is proposed. By certain prepossessing on the measured data of the plant, the interval model identification problem is transformed into several linear programming problems, which can be easily solved through various algorithms. We have proved that the resultant interval model has a known error bound, provided that certain conditions on the measured data are satisfied. To demonstrate its effectiveness, the proposed method is applied to identify the interval model of a servo system with variant load and inertia. © 2.10 AACC.

关键词： Linear programming

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Mobile robot's electronic compass calibration based on modified Fourier Neural Network

Mobile robot's electronic compass calibration based on modif...

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2.11 IEEE 5th International Conference on Robotics, Automation and Mechatronics, RAM 2.11

作者： Kun, Gong Fang, Deng Tao, Ma Beijing 100083 China School of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Beijing 100081 China

ISBN: (纸本)9781612842509

In order to improve the precision of the azimuth measured by mobile robot's electronic compass, this paper proposes a new calibration method based on Fourier Neural Network trained by Modified Particle Swarm Optimization (MPSO-FNN). This method makes use of Fourier Neural Network (FNN) to establish the error compensation model of electronic compass's azimuth, and introduces Modified Particle Swarm Optimization (MPSO) algorithm to optimize the weights of neural network. Thus the comparatively accurate error model of azimuth is obtained to compensate the output of electronic compass. This method not only has strong nonlinear approximation capability, but also overcomes the neural networks' shortcomings which are too slow convergence speed, oscillation, and easy to fall into local optimum and sensitive to the initial values. Experimental results demonstrate that after calibrated by this method, the range of azimuth error reduces to -0.35°-0.70deg;from -3.4°-2..2., and the average value of absolute error is only 0.30°. © 2.11 IEEE.

关键词： Error compensation

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Distributed Optimization and Scaling Design for Solving Sylvester Equations

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Journal of systems Science & complexity 2024年第6期37卷 2487-2510页

作者： CHENG Songsong YU Xin ZENG Xianlin LIANG Shu HONG Yiguang Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and AutomationAnhui UniversityHefei 230601China Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Control Science and Engineering Tongji UniversityShanghai 201804China Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai 201210China

This paper develops distributed algorithms for solving Sylvester *** authors transform solving Sylvester equations into a distributed optimization problem,unifying all eight standard distributed matrix *** the authors propose a distributed algorithm to find the least squares solution and achieve an explicit linear convergence *** results are obtained by carefully choosing the step-size of the algorithm,which requires particular information of data and Laplacian *** avoid these centralized quantities,the authors further develop a distributed scaling technique by using local information *** a result,the proposed distributed algorithm along with the distributed scaling design yields a universal method for solving Sylvester equations over a multi-agent network with the constant step-size freely chosen from configurable ***,the authors provide three examples to illustrate the effectiveness of the proposed algorithms.

关键词： Distributed optimization least squares solution linear convergence rate step-size interval Sylvester equation

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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2.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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Intersection Scan Model and Probability Inference for Vision Based Small-scale Urban Intersection Detection 28

Intersection Scan Model and Probability Inference for Vision...

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IEEE intelligent Vehicles Symposium

作者： Yang Yi Li Hao Zhu Hao Shang Songtian Lyu Ningyi Song Wenjie School of Automation and State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology

ISBN: (纸本)9781509048052

Large-scale intersections stamped on maps have diverse visual features for detection, while small-scale urban intersections are hard to be identified especially when GPS signals are missing. In this paper, we propose a Hidden Markov Model (HMM) based small-scale intersection detection method utilizing monocular vision. We extract visual cues of road transformations and dynamic vehicles' tracks, and then design an Intersection Scan Model to obtain the potential traversable direction of the current road, which is the primary criterion of the intersection estimation. For better performances, we take the detections of consecutive frames into consideration and finally integrate them into HMM to estimate the probabilities of intersections. Results from KITTI datasets and real-world experiments have shown the functionality of the presented approach.

关键词： Hidden Markov models Roads Global Positioning system Vehicle dynamics Semantics Image segmentation Feature extraction

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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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2.13 7th International Conference on Image and Graphics, ICIG 2.13

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. © 2.13 IEEE.

关键词： Vehicles

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Target Assignment Optimization of Heterogeneous Sensor Networks in Urban Environment 39

Target Assignment Optimization of Heterogeneous Sensor Netwo...

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39th Chinese control Conference, CCC 2.2.

作者： Chen, Chen Zihao, Cheng Wei, Xu Beijing Institute of Technology School of Automation Beijing100081 China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing100081 China

ISBN: (纸本)9789881563903

Preventing and controlling Low-Slow-Small(LSS) targets are problems to be solved due to their good concealment in urban environment. Consequently, the problem of target assignment is studied in this paper. Firstly, a target assignment model based on heterogeneous sensor networks is proposed. The characteristics of LSS targets and the influence of environmental factors such as climate and terrain are considered on this model. At the same time, the detection capabilities of different detection nodes and collaborative tracking capabilities are also considered. Secondly, an intelligent optimization algorithm GSAPSO based on PSO is proposed to maximize tracking effect of the sensors. Finally, the simulations are used to compare the GSAPSO algorithm with the traditional PSO and GAPSO algorithms. The results demonstrate that the proposed algorithm has better tracking effect. © 2.2. Technical Committee on control Theory, Chinese Association of Automation.

关键词： Particle swarm optimization (PSO)

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Impedance control with New Inner Torque loop for Compliant Joints and Its Performance Analysis 36

Impedance Control with New Inner Torque loop for Compliant J...

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第36届中国控制会议

作者： Yin Ke Jian Li Zonglin Huang Shuai Li Guodong Li The Bionic Robot and System Key Laboratory School of Mechatronic EngineeringBeijing Institute of Technology Key Laboratory for Intelligent Control and Decision on Complex Systems School of AutomationBeijing Institute of Technology Beijing Jingwei Hirain Technologies

ISBN: (纸本)9781538629185

For the purpose of enhancing compliance of robot joint,an impedance control strategy with new inner torque controller is *** inertia of the motor can be scaled down thanks to this new type of torque *** of different position（motor-side position 9 and link-side position q） feedback strategies are explored through theoretical deviation,simulation and static stiffness *** expressions of static stiffness under both position feedback strategies are obtained with validity verified by Simulink *** with 9 feedback strategy,static stiffness can exceed spring stiffness under q feedback strategy with high desired stiffness,which means wider variation range of static stiffness and this benefits robot applications that require wider variation range of impedance,such as rehabilitation robots and collaborative ***,several experiments with the compliant joint prototype verify the developed controllers and show the efficiency of the proposed control approach in terms of compliant behavior.

关键词： Compliant joint Impedance control Static stiffness

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Medical image segmentation using mean shift algorithm and general edge detection

Medical image segmentation using mean shift algorithm and ge...

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作者： Lu, Jinghua Chen, Jie Zhang, Juan Zou, Lihui 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

ISBN: (纸本)9783902661937

The segmentation of the medical image faces the challenges of the existence of large number of diverse structures of human anatomy and inevitable artifacts induced from the imaging procedure. In this paper we treat some structures and artifacts as general edge features, and introduce the edge information into the mean shift segmentation algorithm in both clustering and the fusion steps. Considering the medical images as two dimensional signals, the general edge can be detected and described with its local spatial frequency properties. The segmentation results show the improvement in preserving the completeness of details while sketching the overall structures. © 2.11 IFAC.

关键词： Image segmentation

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