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Asian control Conference

作者： Yuan Huang Junzheng Wang Dawei Shi Jian Xue State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing P. R. China Harvard John A. Paulson School of Engineering & Applied Sciences Harvard University Cambridge MA USA

ISBN: (纸本)9781509015740;9781509015733

The problem of sampled-data state observation is considered in this work. A nonlinear continuous-time system with internal uncertainty and external disturbance is introduced, for which the sampled-data observation problem based on an extended state observer is formulated. We first introduce the framework of the observed system, in which the output measurement is sampled and transmitted to extended state observer periodically. Then based on this framework, the observation performance of the sampled-data extended state observer (SD-ESO) is investigated. For the observer considered, the uniformly ultimately bounded property has been guaranteed. Furthermore, a co-design method for the sample interval and high gain parameter of SD-ESO is provided to achieve the desired observation performance. The obtained theoretic results are validated through the numerical simulations.

关键词： Observers Uncertainty Networked control systems Convergence Distributed databases Gold Australia

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Semantic motion segmentation for urban dynamic scene understanding

Semantic motion segmentation for urban dynamic scene underst...

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2016 IEEE International Conference on Automation Science and Engineering, CASE 2016

作者： Fan, Qiu Yi, Yang Hao, Li Mengyin, Fu Shunting, Wang School of Automation State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781509024094

A mount of recent researches on scene parsing and semantic labeling, while few focus on obtaining joint semantic motion labeling. In this paper, we propose an approach to infer both the object class and motion status for each pixel of images. First, we extract and match sparse image features to estimate ego-motion between two consecutive stereo images, the result of feature points grouping is used to segment moving object in U-disparity map. Second, a Fully Convolutional Neural Network is employed for semantic segmentation. Moreover, semantic cues are utilized to remove pixels have no potential to be moved in motion mask. Finally, we use a fully connected CRF to integrate motion into semantic segmentation. To validate the effectiveness of the proposed algorithm, we present experimental results with KITTI stereo images that contain moving objects. © 2016 IEEE.

关键词： Semantics

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Solving Large-scale systems of Random Quadratic Equations via Stochastic Truncated Amplitude Flow

Solving Large-scale Systems of Random Quadratic Equations vi...

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European Signal Processing Conference

作者： Gang Wang Georgios B. Giannakis Jie Chen Dept. of ECE and Digital Tech. Center Univ. of Minnesota Mpls MN USA State Key Lab of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

This work develops a new iterative algorithm, which is called stochastic truncated amplitude flow (STAF), to recover an unknown signal x ∈ R~n from m "phaseless" quadratic equations of the form ψ_i = |a_i~T x|, 1 ≤ i ≤ m. This problem is also known as phase retrieval, which is NP-hard in general. Building on an amplitude-based nonconvex least-squares formulation, STAF proceeds in two stages: s1) Orthogonality-promoting initialization computed using a stochastic variance reduced gradient algorithm;and, s2) Refinements of the initial point through truncated stochastic gradient-type iterations. Both stages handle a single equation per iteration, therefore lending STAF well to Big Data applications. Specifically for independent Gaussian {a_i}_(i=1)~m vectors, STAF recovers exactly any x exponentially fast when there are about as many equations as unknowns. Finally, numerical tests demonstrate that STAF improves upon its competing alternatives.

关键词： Stochastic processes Signal processing algorithms Runtime Mathematical model Computational complexity Europe Signal processing

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Distributed trajectory tracking control for multiple nonholonomic mobile robots

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IFAC-PapersOnLine 2016年第4期49卷 31-36页

作者： Yang, Qingkai Fang, Hao Cao, Ming Chen, Jie School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China Faculty of Mathematics and Natural Sciences University of Groningen Groningen AG9747 Netherlands

In this paper, the distributed tracking problem for multiple nonholonomic mobile robots is investigated, in which the nonholonomic models are transformed into chained-form systems. By utilizing the dynamic oscillator strategy, the distributed controllers are constructed such that all the mobile robots' trajectories converge to the desired reference asymptotically. One advantage of the chained-form system solution that we propose is that it requires no other variable transformations, which could help reducing the system's complexity and broadening the proposed controller's practical applications. Simulations are presented to show the effectiveness of the proposed control algorithms. © 2016, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Multi agent systems controllers Distributed parameter control systems Mobile robots Navigation Chained form system Distributed control Distributed controller Distributed tracking Non holonomic mobile robots Tracking controls Trajectory tracking control Variable transformation

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Event-triggered High-gain Observer Design for Nonlinear systems

Event-triggered High-gain Observer Design for Nonlinear Syst...

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第35届中国控制会议

作者： Yuan Huang Junzheng Wang Dawei Shi State Key Laboratory of Intelligent Control and Decision of Complex Systems

ISBN: (纸本)9781509009107

In this work,an event-triggered high gain observer（ET-HGO） design is considered for a continuous-time nonlinear system combined with disturbance and *** the event-trigger scheme,the performance of the ET-HGO depends on the triggering condition ***,in this work,for the high-gain observer considered,an event-triggered transmission strategy,which does not relies on the other system state but the output of the control system,is proposed such that the observation error is asymptotically ***,with mild restriction,the observation error is guaranteed to be bounded all the *** obtained theoretical results are evaluated through the numerical simulations.

关键词： High-gain observer event-triggered transmission state estimation

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Distributed computation of linear matrix equations: An optimization perspective

arXiv

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arXiv 2017年

作者： Zeng, Xianlin Liang, Shu Hong, Yiguang Chen, Jie Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Ministry of Education Beijing100081 China

This paper investigates the distributed computation of the well-known linear matrix equation in the form of AXB = F, with the matrices A, B, X, and F of appropriate dimensions, over multiagent networks from an optimization perspective. In this paper, we consider the standard distributed matrix-information structures, where each agent of the considered multi-agent network has access to one of the sub-block matrices of A, B, and F. To be specific, we first propose different decomposition methods to reformulate the matrix equations in standard structures as distributed constrained optimization problems by introducing substitutional variables;we show that the solutions of the reformulated distributed optimization problems are equivalent to least squares solutions to original matrix equations;and we design distributed continuous-time algorithms for the constrained optimization problems, even by using augmented matrices and a derivative feedback technique. Moreover, we prove the exponential convergence of the algorithms to a least squares solution to the matrix equation for any initial condition. Copyright © 2017, The Authors. All rights reserved.

关键词： Continuous time systems

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Event-based H∞filtering for networked singular systems 35

Event-based H∞filtering for networked singular systems

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35th Chinese control Conference, CCC 2016

作者： Song, Weixu Sun, Jian Chen, Jie School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9789881563910

In this paper, the problem of H∞filtering for networked singular systems with an event-triggered scheme is investigated. With a modified event generator, remote sensor evaluates the periodically sampled data and only transmits those violate a certain event-triggered condition, and thus reduces the communication burden. The filtering error system is converted into a time-delay system model which can be studied using the Lyapunov stability theory. Based on this model, sufficient criteria are derived to guarantee the filtering error system regular, impulse free and stable with a prescribed H∞performance. The design method of the filter is also considered. Finally, an example is exploited to illustrate the effectiveness of the proposed method. © 2016 TCCT.

关键词： Event-triggered communication H∞ filtering Network-induced delay Singular system

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Self adaptation of chimera states

arXiv

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arXiv 2018年

作者： Yao, Nan Huang, Zi-Gang Ren, Hai-Peng Grebogi, Celso Lai, Ying-Cheng Department of Applied Physics Xi’an University of Technology Xi’an710048 China School of Life Science and Technology Xi’an Jiao Tong University Xi’an710049 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China Institute for Complex Systems and Mathematical Biology King’s College University of Aberdeen AberdeenAB24 3UE United Kingdom School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States Department of Physics Arizona State University TempeAZ85287 United States

Chimera states in spatiotemporal dynamical systems have been investigated in physical, chemical, and biological systems, and have been shown to be robust against random perturbations. How do chimera states achieve their robustness? We uncover a self-adaptation behavior by which, upon a spatially localized perturbation, the coherent component of the chimera state spontaneously drifts to an optimal location as far away from the perturbation as possible, exposing only its incoherent component to the perturbation to minimize the disturbance. A systematic numerical analysis of the evolution of the spatiotemporal pattern of the chimera state towards the optimal stable state reveals an exponential relaxation process independent of the spatial location of the perturbation, implying that its effects can be modeled as restoring and damping forces in a mechanical system and enabling the articulation of a phenomenological model. Not only is the model able to reproduce the numerical results, it can also predict the trajectory of drifting. Our finding is striking as it reveals that, inherently, chimera states possess a kind of "intelligence" in achieving robustness through self adaptation. The behavior can be exploited for controlled generation of chimera states with their coherent component placed in any desired spatial region of the system. Copyright © 2018, The Authors. All rights reserved.

关键词： Dynamical systems

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Power system state estimation via feasible point pursuit: Algorithms and Cramér-Rao bound

arXiv

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arXiv 2017年

作者： Wang, Gang Zamzam, Ahmed S. Giannakis, Georgios B. Sidiropoulos, Nicholas D. Digital Tech. Center ECE Dept. U. of Minnesota MplsMN55455 United States State Key Lab. of Intelligent Control and Decision of Complex Systems Beijing Inst. of Tech. Beijing100081 China

Accurately monitoring the system's operating point is central to the reliable and economic operation of an electric power grid. Power system state estimation (PSSE) aims to obtain complete voltage magnitude and angle information at each bus given a number of system variables at selected buses and lines. Power flow analysis is a special case of PSSE, and amounts to solving a set of noise-free power flow equations. Physical laws dictate quadratic relationships between available quantities and unknown voltages, rendering general instances of power flow and PSSE nonconvex and NP-hard. Past approaches are largely based on gradient-type iterative procedures or semidefinite relaxation (SDR). Due to nonconvexity, the solution obtained via gradienttype schemes depends on initialization, while SDR methods do not perform as desired in challenging scenarios. This paper puts forth novel feasible point pursuit (FPP)-based solvers for power flow and PSSE, which iteratively seek feasible solutions for a nonconvex quadratically constrained quadratic programming (QCQP) reformulation of the weighted least-squares (WLS) problem. Relative to the prior art, the developed solvers offer superior performance at the cost of higher complexity. Furthermore, they converge to a stationary point of the WLS problem. As a baseline for comparing different estimators, the Cramér-Rao lower bound (CRLB) is derived for the fundamental PSSE problem in this paper. Judicious numerical tests on several IEEE benchmark systems showcase markedly improved performance of our FPPbased solvers for both power flow and PSSE tasks over popular WLS-based Gauss-Newton iterations and SDR approaches. Copyright © 2017, The Authors. All rights reserved.

关键词： state estimation

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A Navigation Map Building Algorithm using Refined RBPF-SLAM

A Navigation Map Building Algorithm using Refined RBPF-SLAM

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2016 IEEE Chinese Guidance, Navigation and control Conference (IEEE CGNCC2016)

作者： Mengyin Fu Hao Zhu Yi Yang Meiling Wang Zhihong Deng State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institution of Technology

ISBN: (纸本)9781467383196

This paper proposes a map building algorithm for navigation task of autonomous vehicle.A local 2D grid map is designed to convey three types of information(free space,obstacle and unknown).A refined RBPF-SLAM algorithm is established to build a large scale,accurate navigation *** obstacle information is excluded in the final map,which provides better performance in vehicle's online *** sets of experiments are carried out in two driving conditions,with one in urban traffic environment and the other in unstructured *** mapping and localization result testify the effectiveness of our algorithm.

关键词： frame A Navigation Map Building Algorithm using Refined RBPF-SLAM

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