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2006 2nd International Conference on Power Electronics systems and Applications, ICPESA

作者： Lei, Dong Dong, Yang Xiaozhong, Liao Department of Automatic Control Engineering Beijing Institute of Technology Beijing China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing China

ISBN: (纸本)9623675445

In the high speed range, vector control of rotor flux orientation of an induction machine implements good perfornance. However, the perfornance in low speed rang deteriorates because of the inaccurate estimation of rotor flux and speed. In this paper, modified voltage model for rotor flux estimation and neuron model-reference adaptive system (MARS) for speed estimation are used to improve the perfornance of speed sensorless vector control. To improve the accuracy of rotor flux estimation, the stator resistance is identified on-line. The experimental results show that the proposed scheme yields improved perfornance in low speed range.

关键词： Induction machine

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Autonomous Tracking control for Four-Wheel Independent Steering Robot Based on Improved Pure Pursuit

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Journal of Beijing Institute of Technology 2020年第4期29卷 466-473页

作者： Jing Li Qingbin Wu Junzheng Wang Hui Qin Jiehao Li Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information TechnologySchool of AutomationBeijing Institute of TechnologyBeijing 100081China

Autonomous tracking control is one of the fundamental challenges in the field of robotic autonomous navigation,especially for future intelligent *** this paper,an improved pure pursuit control method is proposed for the path tracking control problem of a four-wheel independent steering *** on the analysis of the four-wheel independent steering model,the kinematic model and the steering geometry model of the robot are *** the path tracking control is realized by considering the correlation between the look-ahead distance and the velocity,as well as the lateral error between the robot and the reference *** experimental results demonstrate that the improved pure pursuit control method has the advantages of small steady-state error,fast response and strong robustness,which can effectively improve the accuracy of path tracking.

关键词： autonomous tracking control four-wheel independent steering robot pure pursuit lateral error

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Design of Modular Humanoid Rehabilitation Robot for Apoplectic Hemiplegia 29

Design of Modular Humanoid Rehabilitation Robot for Apoplect...

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第29届中国控制与决策会议

作者： Shuai Li Jian Li Siqi Li Guodong Li Yu Mu The Bionic Robot and System Key Laboratory School of Mechatronical EngineeringBeijing Institute of Technology Key Laboratory for Intelligent Control and Decision on Complex Systems School of AutomationBeijing Institute of Technology

ISBN: (纸本)9781509046584

Stroke is mainly caused by the brain damage due to the acute cerebral vascular disease and its primary disease,which can make upper limb or lower limb on one side of the body *** rehabilitation training is the most effective way to regain the Activities of Daily Living(ADL).Based on the concept of humanoid and modular design,this paper outlines the design process of humanoid ***,kinematics and dynamics are calculated in different coordinate frames,which makes simulation and control algorithms are more complex and not intuitive,for the forked-tree structure rehabilitation robot,a modified geometric description method of DH parameters is proposed to solve the problem of inconsistent frames,the whole body Jacobian matrix of this structure is derived and used for the inverse kinematics,and the singular configurations of redundant manipulator are *** important design criteria of humanoid robot is discussed,and the realization of the mechanical design is ***,the experimental results show that the humanoid robot can effectively carry out multiple parts rehabilitation training.

关键词： Rehabilitation Robot Humanoid robot Modularity Singularity Geometric Representation

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Study on GIS's application in driving in the unstructured environment for UGV

Study on GIS's application in driving in the unstructured en...

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2013 International Conference on Geo-Informatics in Resource Management and Sustainable Ecosystem, GRMSE 2013

作者： Yang, Qiangrong Wang, Meiling School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Intelligent Control and Decision of Complex System Beijing 100081 China

ISBN: (纸本)9783642419072

For UGV, driving in the unstructured environment safely and quickly without human intervention becomes increasingly important. While many scholars have conducted researches in driving in this case, the results seem quite unsatisfied. In this paper, how to use GIS in aiding the UGV to drive in the unstructured environment is studied. First, GIS is used to process the raw data received from the 3D laser scanner to get the high-resolution gradient and elevation grid, which is used to determine the traversability of the environment. Then the relatively low-resolution gradient grid is used as the cost field in the path planning algorithm to generate the optimal path from the start point to the goal point. At last, an algorithm is introduced to get the reference speed limit from the given optimal path according to the geometry features of the path and the gradient grid. Simulation and experiment results are given to show the effectiveness of the algorithms. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Motion planning

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Model predictive control for UGV trajectory tracking based on dynamic model

Model predictive control for UGV trajectory tracking based o...

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2016 IEEE International Conference on Information and Automation, IEEE ICIA 2016

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. © 2016 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. © 2010 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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2011 IEEE 5th International Conference on Robotics, Automation and Mechatronics, RAM 2011

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°-25.2°, and the average value of absolute error is only 0.30°. © 2011 IEEE.

关键词： Error compensation

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Interval analysis for neural networks with application to fault detection

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Science China(Information Sciences) 2024年第11期67卷 222-237页

作者： Zhenhua WANG Youdao MA Song ZHU Thach Ngoc DINH Yi SHEN Department of Control Science and Engineering Harbin Institute of Technology National Key Laboratory of Complex System Control and Intelligent Agent Cooperation School of Mathematics China University of Mining and Technology The CEDRIC-Lab Conservatoire National des Arts et Métiers (CNAM)

This paper investigates an interval analysis method for neural networks and applies it to fault detection for systems with unknown but bounded measurement noise. First, a novel interval analysis method is presented, which can compute the bounds of the output of a feedforward neural network subject to a bounded input. By applying the proposed interval analysis method to a network trained with fault-free system data, adaptive thresholds for fault detection are computed. Finally, one can acquire fault detection results via a fault detection strategy. The proposed method can achieve tight bounds of the network output and employ simple operations, which leads to accurate fault detection results and a low computational burden.A numerical simulation and an experiment on an AC servo motor are given to illustrate the effectiveness and superiority of the proposed method.

关键词： interval analysis feedforward neural network fault detection adaptive thresholds

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Fully distributed consensus of second-order multi-agent systems using adaptive event-based control

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Science China(Information Sciences) 2018年第12期61卷 199-201页

作者： Wei ZHU Qianghui ZHOU DANDan WANG Gang FENG Key Lab of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications Key Lab of Industrial Internet of Things & Networked Control Ministry of EducationChongqing University of Posts and Telecommunications Department of Mechanical and Biomedical Engineering City University of Hong Kong

Dear editor,In recent years, the distributed consensus of multiagent systems (MASs) has attracted compelling attention because of its potential applications in many fields such as sensor networks, unmanned aerial vehicle (UAV) formation flying, and multiple signals tracking. The central task in the distributed consensus of MASs is to design distributed control protocols to achieve the consensus

关键词： In MAS Fully distributed consensus of second-order multi-agent systems using adaptive event-based control

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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25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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