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第37届中国控制会议

作者： Jia-Rong Li Ming-Gang Gan Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision (Beijing Institute of Technology) Ministry of Education

In this paper, we extend perfect tracking control to nonlinear systems, and propose a novel robust perfect tracking control（RPTC） strategy for nonlinear servo tracking systems. The overall control system consists of four parts: a model-based friction compensator, a feedforward perfect tracking controller, an improved internal model controller as the feedback controller,and a disturbance observer for position feedback. First, the friction compensator is introduced to compensate the nonlinear dynamic friction, and the feedforward perfect tracking controller is applied to widen the frequency band. Then, the internal model controller with a differentiator is adopted to yield improved tracking accuracy. Moreover, by utilizing the disturbance observer, the robustness against external disturbances and plant uncertainties is ensured. Finally, high accuracy tracking and ideal robustness are achieved by the RPTC scheme. The stability of the closed loop system is analyzed. Simulation results demonstrate that the proposed RPTC strategy significantly improves the tracking accuracy and enhances the robustness.

关键词： Perfect Tracking control Nonlinear Servo Systems Friction Compensation Disturbance Observer Internal Model control

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Stabilization of Systems Under Stochastic Clock Offsets

Stabilization of Systems Under Stochastic Clock Offsets

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International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Haoyuan Sun Jie Chen Jian Sun Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing P.R. China

ISBN: (纸本)9781538670897;9781538670880

This paper is concerned with the stabilization of networked control systems under clock offsets between sensors and controllers where the clock offsets are assumed to be stochastic variables following a certain probability distribution. A linear time-invariant controller is designed to deal with the effects of the stochastic offsets between sensors and controllers clocks, which can guarantee the stochastic stability of the linear systems. Finally, the validity of our results is illustrated using a numerical simulation.

关键词： Clocks Stability analysis Linear matrix inequalities Sensor systems Stochastic processes Linear systems

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A New Stability Criterion of Networked Switched control Systems with Unknown Time-Varying Delays

A New Stability Criterion of Networked Switched Control Syst...

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Chinese control Conference (CCC)

作者： Guoliang Chen Jian Sun Zhichuang Wang Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing P.R. China

In this article, the stability of networked switched control systems (NSCSs) with unknown time-varying delays is analyzed. By Taylor series expansion and h-order approximation techniques, NSCSs with unknown time-varying delays is modeled to discrete-time switched polytopic uncertain systems, a new stability criterion is proposed for NSCSs based on a necessary and sufficient nonconservative linear matrix inequalities (LMIs) condition for discrete-time switched polytopic uncertain systems. Finally, a numerical example is presented to show the effectiveness of the proposed method.

关键词： Switches Delays Stability criteria Lyapunov methods Numerical stability Thermal stability

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Flocking of Second-Order Multiagent Systems with Connectivity Preservation Based on Algebraic Connectivity Estimation

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IEEE Transactions on Cybernetics 2017年第4期47卷 1067-1077页

作者： Fang, Hao Wei, Yue Chen, Jie Xin, Bin School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

The problem of flocking of second-order multiagent systems with connectivity preservation is investigated in this paper. First, for estimating the algebraic connectivity as well as the corresponding eigenvector, a new decentralized inverse power iteration scheme is formulated. Then, based on the estimation of the algebraic connectivity, a set of distributed gradient-based flocking control protocols is built with a new class of generalized hybrid potential fields which could guarantee collision avoidance, desired distance stabilization, and the connectivity of the underlying communication network simultaneously. What is important is that the proposed control scheme allows the existing edges to be broken without violation of connectivity constraints, and thus yields more flexibility of motions and reduces the communication cost for the multiagent system. In the end, nontrivial comparative simulations and experimental results are performed to demonstrate the effectiveness of the theoretical results and highlight the advantages of the proposed estimation scheme and control algorithm. © 2017 IEEE.

关键词： Multi agent systems

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Fault Tolerant control for a Class of Nonlinear System based on Active Disturbance Rejection control and RBF Neural Networks 36

Fault Tolerant Control for a Class of Nonlinear System based...

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第36届中国控制会议

作者： Lushan Zhou Liling Ma Junzheng Wang State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology

ISBN: (纸本)9781538629185

In this paper,a fault tolerant control method based on active disturbance rejection control(ADRC) and radial basis function neural network(RBFNN) is proposed for a class of multi-input-multi-output nonlinear system with actuator faults,components faults and sensor *** proposed method does not rely on the plant *** regarding the faults and plant uncertainties as the disturbance,through the observation of extended state observer and the compensation of feedback control signal,this method achieves the fault tolerance control of the plant with component fault and actuator *** sensor faults,in this work,radial basis function neural network is applied to estimate the real output of the *** this output estimation is utilized by active disturbance rejection control to achieve the fault tolerance of ***,the effectiveness of the proposed method is validated by the simulation results of the three-tank system.

关键词： Fault tolerant control active disturbance rejection control radial basis function neural network

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Event-Triggered Nonlinear Model Predictive control with Bounded Disturbances and State-dependent Uncertainties

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IFAC-PapersOnLine 2017年第1期50卷 9308-9314页

作者： Wang M. Sun J. Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing 100081 China

In this paper, two event-triggered nonlinear model predictive control(NMPC) strategies based on Lyapunov function method for discrete-time nonlinear systems with bounded disturbances and state-dependent uncertainties are proposed. The corresponding event-triggered control law is designed and the feasibility is analyzed. Stability of the event-triggered NMPC systems is studied and sufficient stability conditions are obtained. Finally, simulation results show advantages of the two event-triggered strategies on performance and computational burden. © 2017

关键词： event-triggered control,nonlinear model predictive control, Lyapunov function

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Target-Focused Video Stabilization for Human Computer Interaction 29

Target-Focused Video Stabilization for Human Computer Intera...

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第29届中国控制与决策会议

作者： Hao Zhu Qing You Wenjie Chen School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System

ISBN: (纸本)9781509046584

As an important task of video enhancement,a lot of video stabilization methods have been *** in many real-world applications,especially the systems with human-computer interactions,existing methods only remove camera motion in stabilized frames,the remaining object motion will also lead to deviations in manual *** this paper,we collect practical hand drawn bounding boxes which have been shown to contain serious *** we propose a target-focused video stabilization method consisting of a proposal-based detection component and a trackingbased motion estimation *** experiments demonstrate our method can remove camera jitter and target motion simultaneously,and also offer users a friendly and effective way to draw accurate target regions.

关键词： Video Stabilization Human-computer Interactive Object Proposal

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A survey on Lyapunov-based methods for stability of linear time-delay systems

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Frontiers of Computer Science 2017年第4期11卷 555-567页

作者： Jian SUN Jie CHEN School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing 100081 China

Recently, stability analysis of time-delay systems has received much attention. Rich results have been obtained on this topic using various approaches and techniques. Most of those results are based on Lyapunov stability theories. The purpose of this article is to give a broad overview of stabil- ity of linear time-delay systems with emphasis on the more recent progress. Methods and techniques for the choice of an appropriate Lyapunov functional and the estimation of the derivative of the Lyapunov functional are reported in this ar- ticle, and special attention is paid to reduce the conservatism of stability conditions using as few as possible decision vari- ables. Several future research directions on this topic are also discussed.

关键词： time-delay system,ity delay-dependent stability,Lyapunov-Krasovskii functionaldelay-independent stabil-linear matrix inequality,

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An Adaptive Sliding Mode controller with The Exponential and Power Reaching Law for Discrete Systems

An Adaptive Sliding Mode Controller with The Exponential and...

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第37届中国控制会议

作者： Xiaofei Zhang Hongbin Ma Zhuang Li Wenchao Zao School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

With the development of aeronautics and astronautics, the response speed of servo system need be faster. First, In order to improve the dynamic quality of servo system, the exponential and power reaching law, which combines the advantages of the exponential reaching law and the power reaching law, is introduced. Second, the chattering of the sliding mode controller（SMC） with the exponential and power reaching law for discrete systems is investigated. Finally, the adaptive sliding mode controller（ASMC） with the exponential and power reaching law is introduced. The stability of the ASMC with the exponential and power reaching law for discrete systems is analyzed, and the simulation of this approach on one joint of a six degrees of freedom robot is carried out. The experimental results indicate that the ASMC with the exponential and power reaching law is effective in reducing the time of arriving the sliding mode surface. The experimental results also indicate that the ASMC with the exponential and power reaching law may make output error reach zero in a shorter time.

关键词： adaptive sliding mode controller reaching law

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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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第37届中国控制会议

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

Recently deep learning based architectures have been widely deployed in many problems of artificial *** 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 autoencoding 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： Convolutional Neural Network Extreme Learning Machine Features Comparison Visualization

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