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第37届中国控制会议

作者： Wei Shen Min Li Junzheng Wang Changkun Chai Wen Zheng Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology Institute of Software Chinese Academy of Sciences Siemens China LTD

The inverse problem is an essential problem in robot *** order to deal with the inverse kinematic problems of hydraulic quadruped robot,the motion process of a single leg is modeled,simulated and analyzed.A new method based on particle swarm optimization（PSO） is proposed in this paper to overcome low computational efficiency,long calculation time and accumulative *** proposed algorithm is attributed to:1) limit the range of particles initialization;2) select suitable compressibility factors;3) employ linear interpolation method to improve the efficiency of the inverse *** simulation results demonstrate that the developed method can provide enhanced computational efficiency and significantly reduce the calculation time while ensuring the precision requirement,and can also eliminate the accumulative error.

关键词： Inverse kinematics Motion optimization Particle swarm optimization Quadruped robot

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State Estimation and Fault Detection for Nonlinear Dynamic systems

State Estimation and Fault Detection for Nonlinear Dynamic S...

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第37届中国控制会议

作者： Baohua Lu Liping Yan Hongxue Chen Yuanqing Xia Mengyin Fu Bo Xiao Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology School of Information and Communication Engineering Beijing University of Posts and Telecommunications

In practical problems, the dynamic systems are usually nonlinear. In this case, the traditional Kalman filter cannot be used for state estimation or fault detection. The two typical extension based on Kalman filtering framework is the Extended Kalman Filter(EKF) and the Unscented Kalman Filter(UKF). Theoretically speaking, UKF is better than EKF when estimation accuracy is concerned, especially for high degree nonlinear cases. This paper is concerned with the state estimation and fault detection problem for a class of nonlinear dynamic systems. A novel fault detection and analyse method is presented based on the period residual of EKF and UKF. For different kind of faults, mainly, the system parameter error, the sensor/data error, EKF and UKF are used, and the estimation and fault detection effects are compared and analyzed.

关键词： nonlinear system state estimation fault detection parameter error sensor error

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Convolutional Neural Network Features Comparison Between Back-Propagation and Extreme Learning Machine

Convolutional Neural Network Features Comparison Between Bac...

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Chinese control Conference

作者： Atmane Khellal Hongbin Ma Qing Fei School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

Recently deep learning based architectures have been widely deployed in many problems of artificial intelligence. Among deep learning models, Convolutional Neural Networks (CNN) have been reported in numerous successful applications such as object recognition, and natural language processing. The convolutional neural networks are trained by back-propagating the classification error using the Back-Propagation (BP) algorithm, which requires a large amount of data and slows the training process. To overcome these difficulties, a new fast and accurate approach based on Extreme Learning Machine (ELM) to train any convolutional neural network has been proposed. The developed framework (ELM-CNN) is based on the concept of auto-encoding to learn the convolutional filters with biases, by reconstructing the normalized input and the intercept term. In this paper, systematic comparison with traditional back-propagation based training method (BP-CNN) has been made with respect to two aspects qualitative and quantitative. The experimental results on the popular MNIST dataset show that the ELM-CNN algorithm achieves competitive results in terms of generalization performance and up to 16 times faster than the back-propagation based training of CNN.

关键词： Training Convolutional neural networks Feature extraction Computer architecture Convolution Machine learning Encoding

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A smooth double proximal primal-dual algorithm for a class of distributed nonsmooth optimization problem

arXiv

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arXiv 2018年

作者： Wei, Yue Fang, Hao Zeng, Xianlin Chen, Jie Pardalos, Panos M. School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China Industrial and Systems Engineering University of Florida

This technical note studies a class of distributed nonsmooth convex consensus optimization problem. The cost function is a summation of local cost functions which are convex but nonsmooth. Each of the local cost functions consists of a twice differentiable (smooth) convex function and two lower semi-continuous (nonsmooth) convex functions. We call this problem as single-smooth plus double-nonsmooth (SSDN) problem. Under mild conditions, we propose a distributed double proximal primal-dual optimization algorithm. The double proximal operator is designed to deal with the difficulty caused by the unproximable property of the summation of those two nonsmooth functions. Besides, it can also guarantee that the proposed algorithm is locally Lipschitz continuous. An auxiliary variable in the double proximal operator is introduced to estimate the subgradient of the second nonsmooth function. Theoretically, we conduct the convergence analysis by employing Lyapunov stability theory. It shows that the proposed algorithm can make the states achieve consensus at the optimal point. In the end, nontrivial simulations are presented and the results demonstrate the effectiveness of the proposed algorithm. Copyright © 2018, The Authors. All rights reserved.

关键词： Cost functions

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Trajectory Tracking based on Time-Varying Sliding Mode controller for Hypersonic Vehicle with Aileron Stuck 36

Trajectory Tracking based on Time-Varying Sliding Mode Contr...

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第36届中国控制会议

作者： Haibo Ji Lei Wang Zhuoyue Song Xiangdong Liu Zhirong Lei State Key Laboratory of Intelligent Control and Decision of Complex Systems and School of Automation Beijing Institute of Technology School of Automation Northwestern Polytechnical University

ISBN: (纸本)9781538629185

This paper presents nonlinear robust trajectory tracking strategies for the hypersonic vehicle whose ailerons are stuck at an unknown angular position. Firstly, a time-varying sliding mode control strategy for general second-order systems is introduced, and the chattering of sliding mode controller is alleviated. Secondly, the dynamics of hypersonic vehicle are transformed into two second-order systems. Then, the corresponding guidance law and attitude controller are designed using time-varying sliding mode controller. By the proposed strategies, the hypersonic vehicle can fly along the reference ***, the proposed strategies are applied to a hypersonic platform to verify its validity.

关键词： Trajectory Tracking Stuck Aileron Time-Varying Sliding Mode

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An Algorithm for Quadruped Robot's Inverse Kinematic Problems Based on PSO

An Algorithm for Quadruped Robot's Inverse Kinematic Problem...

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Chinese control Conference (CCC)

作者： Wei Shen Min Li Junzheng Wang Changkun Chai Wen Zheng Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing Institute of Software Chinese Academy of Sciences Beijing Siemens China LTD Beijing

The inverse problem is an essential problem in robot kinematics. In order to deal with the inverse kinematic problems of hydraulic quadruped robot, the motion process of a single leg is modeled, simulated and analyzed. A new method based on particle swarm optimization (PSO) is proposed in this paper to overcome low computational efficiency, long calculation time and accumulative error. The proposed algorithm is attributed to: 1) limit the range of particles initialization; 2) select suitable compressibility factors; 3) employ linear interpolation method to improve the efficiency of the inverse algorithm. The simulation results demonstrate that the developed method can provide enhanced computational efficiency and significantly reduce the calculation time while ensuring the precision requirement, and can also eliminate the accumulative error.

关键词： Legged locomotion Robot kinematics Kinematics Trajectory Hip Hydraulic systems

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A Vision and Neural Network Based Air-Ground Coordinated control System

A Vision and Neural Network Based Air-Ground Coordinated Con...

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2017 IEEE International Conference on Unmanned systems (ICUS)

作者： Muyun Jiang Jiahui Shi Hongbin Ma You Li School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781538631089;9781538631072

This paper presents an air-ground coordinated system made up of an Unmanned Aerial Vehicle(UAV) and an Unmanned Ground Vehicle(UGV).The movement of UGV is totally controlled by UAV and multiple sensors are adopted in the system to ensure the stability.A novel neutral network algorithm is introduced to identify the location and orientation of *** component is introduced and tested in detail and the coordinated system performs a satisfying result.

关键词： Air-ground system Neutral Network

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Trajectory tracking of under-actuated reentry vehicle based on time-varying SMC with RBF disturbance observer 5

Trajectory tracking of under-actuated reentry vehicle based ...

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5th International Workshop on Advanced Computational Intelligence and intelligent Informatics, IWACIII 2017

作者： Ji, Haibo Guo, Fuhui Liu, Xiangdong School of Automation State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

In this paper, an effective guidance scheme and a control scheme are proposed to realize trajectory tracking of hypersonic reentry vehicle(HRV) subject to aileron stuck in some position. The overload is adopted as virtual control instead of lift and lateral force, then guidance order can be obtained by torque coefficient function. In attitude subsystem, attack of angle and sideslip angle are controlled to track guidance order. Time-varying sliding mode control method is adopted to design guidance law and attitude controller. Besides, a RBF observer is designed to estimate the unknown external disturbance to soften the chattering caused by TVSMC. Simulations verify the proposed schemes.

关键词： Sliding mode control

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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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Exponential input-to-state stability of stochastic fuzzy delayed Cohen-Grossberg neural networks under impulsive perturbations

Exponential input-to-state stability of stochastic fuzzy del...

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第37届中国控制会议

作者： Weisong Zhou Hao Zeng Donghai Wu Key Lab of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications Key Laboratory of Industrial Internet of Things and Networked Control Ministry of EducationChongqing University of Posts and Telecommunications

In this paper,we study a class of stochastic fuzzy delayed Cohen-Grossberg neural networks under impulsive *** Razumikhin method and iteration technique,some sufficient conditions ensuring the mean-square exponential input-to-state stability of the designed delayed neural networks are *** results can generalize and improve some earlier publications.A numerical example is demonstrated to verify the theoretical results.

关键词： Impulsive Stochastic Cohen-Grossberg neural networks Exponential input-to-state stability

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