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52nd IEEE Conference on decision and control, CDC 2013

作者： SabǍu, Şerban OarǍ, Cristian Warnick, Sean Jadbabaie, Ali Electrical and Computer Engineering Dept. Stevens Institute of Technology United States Faculty of Automatic Control Dept. University Politehnica Bucharest Romania Faculty of Computer Science Department Information and Decision Algorithms Laboratories Brigham Young University United States Faculty of Electrical and Systems Engineering Dept. University of Pennsylvannia United States

ISBN: (纸本)9781467357173

In this paper we study state-space realizations of Linear and Time-Invariant (LTI) systems. Motivated by biochemical reaction networks, Gonçalves and Warnick have recently introduced the notion of a Dynamical Structure Functions (DSF), a particular factorization of the system's transfer function matrix that elucidates the interconnection structure in dependencies between manifest variables. We build onto this work by showing an intrinsic connection between a DSF and certain sparse left coprime factorizations. By establishing this link, we provide an interesting systems theoretic interpretation of sparsity patterns of coprime factors. In particular we show how the sparsity of these coprime factors allows for a given LTI system to be implemented as a network of LTI sub-systems. We examine possible applications in distributed control such as the design of a LTI controller that can be implemented over a network with a pre-specified topology. ©2013 IEEE.

关键词： Factorization

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A Smartphone Localization Algorithm Using RSSI and Inertial Sensor Measurement Fusion

A Smartphone Localization Algorithm Using RSSI and Inertial ...

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IEEE Global Communications Conference

作者： William Wei-Liang Li Ronald A. Iltis Moe Z. Win Department of Electrical and Computer Engineering University of California Laboratory for Information and Decision Systems Massachusetts Institute of Technology

ISBN: (纸本)9781479913510

Indoor navigation using the existing wireless infrastructure and mobile devices is a very active research area. The major challenge is to leverage the extensive smartphone sensor suite to achieve location tracking with high accuracy. In this paper, we develop a navigation algorithm which fuses the WiFi received signal strength indicator (RSSI) and smartphone inertial sensor measurements. A sequential Monte Carlo filter is developed for inertial sensor based tracking, and a radiolocation algorithm is developed to infer mobile location based on RSSI measurements. The simulation results show that the proposed algorithm significantly outperforms the extended Kalman filter (EKF), and achieves competitive location accuracy compared with the round trip time (RTT) based ultra-wideband (UWB) system.

关键词： Indoor navigation Smartphone localization Inertial measurement unit (IMU) Particle filter Information fusion Received Signal Strength Indicator Information fusion Indoor navigation Particle filters Smartphone Inertial Location tracking Sensors positioning accuracy Wi-Fi

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Reconstruction of directed acyclic networks of dynamical systems

Reconstruction of directed acyclic networks of dynamical sys...

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American control Conference

作者： Donatello Materassi Murti V. Salapaka Laboratory for Information and Decision Systems Massachusetts Institute of Technology Department of Electrical and Computer Engineering University of Minnesota

ISBN: (纸本)9781479901777

Determining the relation structure of various interconnected entities from multiple time series data is of significant interest to many areas. Knowledge of such a structure can aid in identifying cause and effect relationships, clustering of similar entities, detecting representative elements for an aggregate and determining reduced order models. Current methods tend to treat observations in a static manner by modeling the measured time series as repeated realizations of as many random variables that are independent over time. This amounts to assume static relationships among the measurements, making these techniques ill-suited for detecting propagative and dynamic phenomena that can be fundamental for the understanding of the system. In this paper we extend techniques for the identification of networks of random variables connected through static relations to the case of random processes with dynamic relations. This is achieved by showing that the Wiener filter defines a relationship among jointly stationary stochastic processes that has the properties of a semi-graphoid.

关键词： acyclic network Random variable DYNAMICAL systems Stochastic Processes Wiener filters dynamic phenomenon time series data Reduced order model Mentoring

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Global output feedback stabilization for a class of nonlinear planar systems with output-dependent growth rates

Global output feedback stabilization for a class of nonlinea...

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3rd IFAC Conference on Intelligent control and Automation Science, ICONS 2013

作者： Wang, Xiangyu Qian, Chunjiang Li, Shihua School of Automation Southeast University Nanjing 210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education China Department of Electrical and Computer Engineering University of Texas at San Antonio San Antonio TX 78249 United States

ISBN: (纸本)9783902823458

In this paper, we consider the global output feedback stabilization problem for a class of nonlinear planar systems under a more general growth condition. The nonlinearities in such a system are bounded by both lower-order and higher-order terms with an output-dependent growth rate. This problem is solved by integrating the feedback domination technique and a novel dual observer approach, where two individual observers are constructed in parallel with one estimating the linear part of the unmeasurable state and the other estimating the higher-order part. Moreover, the presented observers and the output feedback controller all have nonlinear gains. Simulations illustrate the effectiveness of the proposed stabilization scheme. Copyright © 2013 IFAC.

关键词： Growth rate

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Diagonal and Low-Rank Decompositions and Fitting Ellipsoids to Random Points

Diagonal and Low-Rank Decompositions and Fitting Ellipsoids ...

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IEEE Annual Conference on decision and control

作者： James Saunderson Pablo A. Parrilo Alan S. Willsky Laboratory for Information and Decision Systems Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA 20139 USA

ISBN: (纸本)9781467357159

Identifying a subspace containing signals of interest in additive noise is a basic system identification problem. Under natural assumptions, this problem is known as the Frisch scheme and can be cast as decomposing an n × n positive definite matrix as the sum of an unknown diagonal matrix (the noise covariance) and an unknown low-rank matrix (the signal covariance). Our focus in this paper is a natural class of random instances, where the low-rank matrix has a uniformly distributed random column space. In this setting we analyze the behavior of a well-known convex optimization-based heuristic for diagonal and low-rank decomposition called minimum trace factor analysis (MTFA). Conditions for the success of MTFA have an appealing geometric reformulation as finding a (convex) ellipsoid that exactly interpolates a given set of n points. Under the random model, the points are chosen according to a Gaussian distribution. Numerical experiments suggest a remarkable threshold phenomenon: if the (random) column space of the n × n low-rank matrix has codimension as small as 2n~(1/2) then with high probability MTFA successfully performs the decomposition task, otherwise it fails with high probability. In this work we provide numerical evidence and prove partial results in this direction, showing that with high probability MTFA recovers such random low-rank matrices of corank at least cn~β for β ∈ (5/6, 1) and some constant c.

关键词： Diagonal Column space Random Additive noise Gaussian distribution

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Experimental Testing of a Traction control System with On-line Road Condition Estimation for Electric Vehicles

Experimental Testing of a Traction Control System with On-li...

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Mediterranean Conference on control & Automation

作者： Goran Vasiljevic Karlo Griparic Stjepan Bogdan LARICS - Laboratory for Robotics and Intelligent Control Systems Department of Control and Computer Engineering. Faculty of Electrical Engineering and Computing University of Zagreb

ISBN: (纸本)9781479909964

In this paper experimental results of testing slip-based traction control system (TCS) with an on-line road condition estimation are presented. TCS is designed for a car with in-wheel electric motors, so that estimation and control are implemented independently for each wheel thus enabling the optimal friction coefficient for every wheel, even if they are on different surfaces or have different tire characteristics. A road condition is approximated using a function which is estimated in the real-time and used as the input to the TCS. The design of the presented TCS is based on the wheel slip ratio, controlled to it's optimal value by a PI controller and with the addition of a feedforward branch for the transition response speed up. System is tested on a newly developed experimental setup consisting of the wheel with embedded (in-wheel) motor rolling on the metal drum loaded by the second motor simulating car behaviour.

关键词： Traction control systems Pavement condition Electric vehicles Wheels PI control coefficient of friction experimental test SLIP RATIO Cars Best value IN-LINE

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Transient Response Functions for Graph Structure Addressable Memory

Transient Response Functions for Graph Structure Addressable...

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IEEE Annual Conference on decision and control

作者： Weibo Gong Complex Systems Modeling and Control Laboratory Department of Electrical and Computer Engineering University of Massachusetts Amherst MA 01002 U.S.A.

ISBN: (纸本)9781467357159

While neurons in the brain are individually quite slow, collectively they can recognize concrete objects as well as abstract concepts very quickly. Motivated by this puzzling fact we propose biologically plausible algorithms that are capable of quickly recognizing similar graph structures. Graphs are combinatorial constructions and pose serious challenges to similarity testing. In this paper we use the transient behavior of random walk over graphs to compare their spectral resolution. We collect data from intrinsically parallel random walks to form a graph response function as an effective measure of graph similarity. Our algorithm could be a solution to the long standing mystery of content addressability in the brain.

关键词： Testing Eigenvalues and eigenfunctions Transient analysis Heuristic algorithms Markov processes Heating computers

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Incommensurate order fractional optimal control: Application to treatment of psychiatric disorders

Incommensurate order fractional optimal control: Application...

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Iranian Conference on electrical engineering (ICEE)

作者： S. S. Tabatabaei M. J. Yazdanpanah M. S. Tavazoei Department of Electrical Engineering Amirkabir University of Technology Tehran Iran Advanced Control Systems Laboratory Control and Intelligent Processing Center of Excellence School of Electrical and Computer Tehran Iran Electrical Engineering Department Sharif University of Technology Tehran Iran

ISBN: (纸本)9781467356329

The main point of this paper is to present a time domain strategy for drug dosage to treat psychiatric disorders. A time domain model of emotion is obtained from an extension of a recently developed fractional nonlinear dynamic model of happiness. First, the Fractional Optimal control law for incommensurate multi state systems is obtained. It will be then applied as an optimal drug administration procedure in the line of psychiatric disorders treatment. Results of this paper show that optimal control scheme is a proper approach to face the difficulties of analysis and control the incommensurate systems. It can be also clearly seen from the simulation results that this approach is very effective in the case that control methods are used as treatment techniques.

关键词： Mathematical model Drugs Optimal control Numerical models Differential equations Equations

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Integrated IMU and Radiolocation-based Navigation Using A Rao-Blackwellized Particle Filter

Integrated IMU and Radiolocation-based Navigation Using A Ra...

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IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： William Wei-Liang Li Ronald A. Iltis Moe Z. Win Department of Electrical and Computer Engineering University of California Santa Barbara CA 93106 USA Laboratory for Information and Decision Systems Massachusetts Institute of Technology Cambridge MA 02139 USA

ISBN: (纸本)9781479903573

In this paper, we develop a cooperative IMU/radiolocation-based navigation system, where each node tracks the location not only based on its own measurements, but also via collaboration with neighbor nodes. The key problem is to design a nonlinear filter to fuse IMU and radiolocation information. We apply the Rao-Blackwellization method by using a particle filter and parallel Kalman filters for the estimation of orientation and other states (i.e., position, velocity, etc.), respectively. The proposed method significantly outperforms the extended Kalman filter (EKF) in the set of simulations here.

关键词： Cooperative localization navigation inertial measurement unit (IMU) information fusion particle filter Particle filters navigation Information fusion Nonlinear filters

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Investigation of the Impact of the Upstream Induction Zone on LIDAR Measurement Accuracy for Wind Turbine control Applications using Large-Eddy Simulation

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Journal of Physics: Conference Series 2014年第1期524卷

作者： Eric Simley Lucy Y Pao Pieter Gebraad Matthew Churchfield Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO USA Delft Center for Systems and Control Delft University of Technology Delft The Netherlands National Wind Technology Center National Renewable Energy Laboratory Golden CO USA

Several sources of error exist in lidar measurements for feedforward control of wind turbines including the ability to detect only radial velocities, spatial averaging, and wind evolution. This paper investigates another potential source of error: the upstream induction zone. The induction zone can directly affect lidar measurements and presents an opportunity for further decorrelation between upstream wind and the wind that interacts with the rotor. The impact of the induction zone is investigated using the combined CFD and aeroelastic code SOWFA. Lidar measurements are simulated upstream of a 5 MW turbine rotor and the true wind disturbances are found using a wind speed estimator and turbine outputs. Lidar performance in the absence of an induction zone is determined by simulating lidar measurements and the turbine response using the aeroelastic code FAST with wind inputs taken far upstream of the original turbine location in the SOWFA wind field. Results indicate that while measurement quality strongly depends on the amount of wind evolution, the induction zone has little effect. However, the optimal lidar preview distance and circular scan radius change slightly due to the presence of the induction zone.

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