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第25届中国控制与决策会议

作者： Liang Wang Yongzhi Sheng Xiangdong Liu Jie Geng School of Automation Beijing Institute of Technology Key laboratory for Intelligent Control & Decision of Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781467355339

An optimal time-varying sliding mode controller based on SDRE approach is proposed in this paper for re-entry vehicle attitude control in the presence of parametric uncertainties and external disturbances. Firstly, an optimal time-varying sliding surface is obtained through the minimization of a given performance index function and the philosophy of time-varying sliding mode control. Subsequently, a discontinuous control law is designed for guaranteeing the existence of the sliding mode throughout the entire response of the system. Therefore, the global robustness can be ensured. Simulation example is finally given to illustrate the effectiveness of the proposed controller.

关键词： Re-entry vehicle Attitude control SDRE Optimal time-varying sliding mode control

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Robust control of Spacecraft Eigenaxis Maneuver via Integral Sliding Mode

Robust Control of Spacecraft Eigenaxis Maneuver via Integral...

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第25届中国控制与决策会议

作者： Zhen Chen Binglong Cong Xiangdong Liu School of Automation Beijing Institute of Technology Key Laboratory for Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781467355339

The control problem of spacecraft eigenaxis maneuver in the presence of parametric uncertainty and external disturbance is addressed in this paper. Modified Rodrigues parameters （MRPs） are utilized as the attitude parameters for the non-redundancy. An eigenaxis maneuver control law with feedback and feed-forward terms is presented for the nominal system. The transient response of close loop system can be adjusted according to an approximate second order system. To improve the robustness, integral sliding mode （ISM） technique is adopted to reject undesirable effects and track nominal trajectory. The resulting controller can perform the eigenaxis maneuver in the presence of parametric uncertainty and external disturbance while possess good system performance. The effectiveness of the proposed method is demonstrated by simulation results.

关键词： Rigid Spacecraft Attitude control Eigenaxis Rotation Integral Sliding Mode MRPs

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Observer-based fuzzy control for nonlinear fractional-order systems via fuzzy T-S models: The 1 < α < 2 case

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IFAC Proceedings Volumes 2014年第3期47卷 6086-6091页

作者： Zhe Gao Xiaozhong Liao College of Light Industry Liaoning University Shenyang 110036 P. R. China School of Automation Beijing Institute of Technology Beijing 100081 P. R. China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081 P. R. China

This paper presents observer-based fuzzy control for nonlinear fractional-order systems with the fractional order α satisfying 1 < α < 2 via fuzzy T-S models. Using the properties of the Kronecker product and LMI approach, the feedback and observer gain matrices are designed. By this method, the state of nonlinear system described as the fuzzy T-S model is convergent to the equilibrium and the observer error is convergent to zero. Finally, the simulation result of a numerical example is given to illustrate the effectiveness of this method.

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Chaotic Particle Swarm Optimization Algorithm Parametric Identification of Bouc-Wen hysteresis Model for Piezoelectric Ceramic Actuator

Chaotic Particle Swarm Optimization Algorithm Parametric Ide...

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第25届中国控制与决策会议

作者： Ning Dong Hongjuan Li Xiangdong Liu Key Laboratory for Intelligent Control & Decision of Complex Systems Beijing Institute of Technology School of Automation Beijing Institute of Technology

ISBN: (纸本)9781467355339

A chaotic particle swarm optimization (CPSO) algorithm is proposed by introducing chaos state into the original Particle Swarm Optimization (PSO) which aims to solving the flaws of easy plunging into local optimum and losing search ability in the last period for the fast particle velocity decrease. CPSO algorithm takes advantage of the ergodicity, randomicity, and regularity of chaos to make chaotic searching for the global extremun at the same time with the particle swarm optimization. This algorithm synthesizes the high efficiency of global optimization of PSO algorithm and the ergodicity and randomicity of local search of chaotic algorithm. This paper utilizes aforementioned algorithm to identify the Bouc-Wen hysteresis model for piezoelectric ceramic actuators (PCA). The experimental results show that the model identified by CPSO algorithm has better performance than that by PSO algorithm.

关键词： Chaotic Particle Swarm Optimization Bouc-Wen Identification Piezoelectric Ceramic Actuator

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Non-Gaussian Approximation Iterative Receiver for MIMO-OFDM Vehicular Networks

Non-Gaussian Approximation Iterative Receiver for MIMO-OFDM ...

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17th International IEEE Conference on intelligent Transportation systems & The Asia-Pacific Council on systems Engineering Conference 2014

作者： Shuangshuang Han Liuqing Yang Xiang Cheng Shichao Chen Fenghua Zhu Zhongdong Yu Haitao Xie Qingdao Academy of Intelligent Industries State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Electronics Engineering and Computer Science Peking University Guang Zhou Communication Information Construction Investment and Operation Co.Ltd.

Multiple-Input Multiple-Output- Orthogonal Frequency Division Multiplexing(MIMO-OFDM) is adopted to vehicular networks to increase the capacity,reliability and *** this paper,iterative demodulation and decoding algorithms are studied to approach the capacity of MIMOOFDM vehicular *** analysing the drawbacks of the Gaussian approximation on the interference cancellation,NonGaussian approximation is proposed to enhance the performance of interference cancellation based detectors with large *** results demonstrate that the proposed non-Gaussian algorithm can achieve a significant performance gain over existing ones with high order constellations.

关键词： Gaussian Non-Gaussian Approximation Iterative Receiver for MIMO-OFDM Vehicular Networks

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Decentralized Filtering a Multi-Agent System with Local Parametric Couplings Based On Kalman Filter

Decentralized Filtering a Multi-Agent System with Local Para...

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第25届中国控制与决策会议

作者： Yini Lv Hongbin Ma Mengyin Fu Chenguang Yang Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institution of Technology School of Computing and Mathematics Plymouth University

ISBN: (纸本)9781467355339

In this paper, decentralized filtering of multiagent systems with coupling uncertainties is proposed and investigated. The considered multi-agent system is composed of many agents, each of which evolves with a discrete-time stochastic linear time-varying dynamics, and every agent can be locally influenced by its neighbor agents. Therefore the states evolution of each agent is not only related with its previous states but also related with its neighbors' previous states in the linear dynamic system. Communication limitations existing in the considered multi-agent system restrict that each agent can only observe its own measurements (outputs) and its neighbor agents' outputs while the states are invisible to any agent. Because of communication limitations and information constraints, without knowing the coupling gains of the local interactions, it is not easy for each agent to estimate its states by traditional kalman filter or other state observers, which were extensively discussed in the literature. In this preliminary study, for the considered coupled linear discrete-time multiagent system with uncertain linear local couplings, based on the key idea of state augmentation and the certainty-equivalence principle borrowed from the area of adaptive control, we propose an efficient decentralized kalman filtering scheme, for each agent, to simultaneously estimate the unknown states and coupling parameters, and extensive simulations are conducted, which have clearly verified the effectiveness of the proposed decentralized filtering scheme.

关键词： multi-agent system, kalman filter, parametric couplings, parameter estimation, states estimation, decentralized filtering

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Synchronization in complex networks and its application - A survey of recent advances and challenges

Synchronization in complex networks and its application - A ...

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作者： Tang, Yang Qian, Feng Gao, Huijun Kurths, Jürgen Potsdam Institute for Climate Impact Research Potsdam14473 Germany Institute of Physics Humboldt University of Berlin Berlin12489 Germany Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin150080 China Institute for Complex Systems and Mathematical Biology University of Aberdeen AberdeenAB24 3UE United Kingdom Department of Control Theory Nizhny Novgorod State University Gagarin Avenue 23 Nizhny Novgorod606950 Russia King Abdulaziz University Jeddah21589 Saudi Arabia

complex networks have, in recent years, brought many innovative impacts to large-scale systems. However, great challenges also come forth due to distinct complex situations and imperative requirements in human life nowadays. This paper attempts to present an overview of recent progress of synchronization of complex dynamical networks and its applications. We focus on robustness of synchronization, controllability and observability of complex networks and synchronization of multiplex networks. Then, we review several applications of synchronization in complex networks, especially in neuroscience and power grids. The present limitations are summarized and future trends are explored and tentatively highlighted. © 2014 Elsevier Ltd. All rights reserved.

关键词： Synchronization

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Identification of Linear Parameter Varying systems with Missing Output Data Using Generalized Expectation-Maximization Algorithm

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IFAC Proceedings Volumes 2014年第3期47卷 9364-9369页

作者： X. Yang W. Xiong B. Huang H. Gao Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin Heilongjiang 150080 China Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Jiangnan University Wuxi Jiangsu 214122 China Department of Chemical and Materials Engineering University of Alberta Edmonton Alberta T6G 2G6 Canada Research Institute of Mechatronics and Automation Bohai University Jinzhou 121013 China and Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin Heilongjiang 150080 China

This paper is concerned with the identification problems of linear parameter varying (LPV) systems with randomly missing output data. Since one local linearized model cannot capture the global dynamics of the nonlinear industrial process, the multiple-model LPV model in which the global model is constructed by smoothly weighted combination of multiple local models is considered here. The problem of missing output variables data is commonly encountered in practice. In order to handle the multiple-model identification problems of LPV systems with incomplete data, the local model is taken to have a finite impulse response (FIR) model structure and the generalized expectation-maximization (EM) algorithm is adopted to estimate the unknown parameters of the global LPV model. To avoid the problems of ill-conditioned matrices and high sensitivity of parameters to noise, the prior information on the coefficients of each local FIR model is employed to construct the prior probability of unknown parameters. Then the maximum a posteriori (MAP) estimates of the global model parameters are derived via the generalized EM algorithm. The numerical example is presented to demonstrate the effectiveness of the proposed method.

关键词： Linear parameter varying systems Generalized EM algorithm Missing output data Maximum a posteriori estimates

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Sensor fault detection with online sparse least squares support vector machine

Sensor fault detection with online sparse least squares supp...

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32nd Chinese control Conference, CCC 2013

作者： Su, Guo Fang, Deng Jian, Sun Li, Fengmei School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081 China

ISBN: (纸本)9789881563835

In this paper, we present the theory of online sparse least squares support vector machine (OS-LSSVM) for prediction and propose a predictor with OS-LSSVM to detect sensor fault. The principle of the predictor and its online algorithm are introduced. Compared with the traditional least squares support vector machine (LSSVM), OS-LSSVM has an advantage on training speed owing to the online training algorithm based on the base vector set. The real-time output data of sensor is employed as the training vector to establish the regression model. This method is compared with the LSSVM predictor in the experiment. Three typical faults of sensors are investigated and the simulation result indicates that the OS-LSSVM predictor can diagnose sensor fault accurately and rapidly, thus it is especially suitable for online sensor fault detection. © 2013 TCCT, CAA.

关键词： Vectors

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一种仿生水下机器人的设计与动力学分析(英文)

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自动化学报 2013年第8期39卷 1330-1338页

作者： WEI Qing-Ping WANG Shuo DONG Xiang SHANG Liu-Ji TAN Min The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Institute of Intelligent Machines Chinese Academy of Sciences

A biomimetic underwater vehicle propelled by two undulating long-fins is introduced in this paper. The concerned vehicle is propelled by two symmetrical undulating long-fins installed on both sides. Ten servo motors are employed to drive the long-fins and cosine wave function is employed for motor control. A real-time control system is designed for controlling the long-fins by adjusting its oscillating frequency and oscillating amplitude. An inertial measurement unit is installed to collect the accelerations and angular velocity. To obtain the relationship between oscillating frequency/amplitude and swimming performance, kinematic analysis and hydromechanic analysis are given. By dividing the long-fin into many small elements and computing the hydrodynamic force acting on each element, the instantaneous thrust generated by the long-fin is obtained. Then the average thrust of the long-fin is obtained by summing up the forces acted on the elements in one undulating period. Then swimming experiments are carried out to validate the vehicle design and kinematic analysis and hydromechanic analysis. And two swimming motion modes including marching and rotating locomotion are chosen. Finally, discussions between the swimming performance and the oscillating parameters are given.

关键词：水下机器人车辆设计动力学分析起伏仿生鳍计算流体动力学运动学分析

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