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AIAA Guidance, Navigation, and control Conference 2015, MGNC 2015 - Held at the AIAA SciTech Forum 2015

作者： Abdelghaffar, Hossam Woolsey, Craig A. Ali, Hesham Arafat Bradley Department of Electrical & Computer Engineering Virginia Tech BlacksburgVA United States Department of Computers & Control Systems Faculty of Engineering Mansoura University Mansoura Egypt Department of Aerospace and Ocean Engineering Virginia Tech BlacksburgVA United States

ISBN: (纸本)9781510801097

In this paper we address the problem of estimating the source location of an airborne biological agent in a turbulent wind field using an unmanned aircraft system (UAS) and Bayesian occupancy grid mapping. The UAS is assumed to fly at constant altitude and is capable of measuring the contaminant concentration using a biological sensor. In simulations, a turbulent wind simulator is used to propagate a plume of contaminant being released from an unknown source location. Recursive Bayesian estimation is applied to estimate the source location. An occupancy grid map gives the probability that a given grid cell contains the source. The grid is updated in response to detection events in order to guide the UAS toward the source. © 2015, E-flow American Institute of Aeronautics and Astronautics (AIAA). All rights reserved.

关键词： Bayesian networks

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Network aggregative games: Distributed convergence to Nash equilibria

Network aggregative games: Distributed convergence to Nash e...

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IEEE Annual Conference on Decision and control

作者： Francesca Parise Basilio Gentile Sergio Grammatico John Lygeros Automatic Control Laboratory ETH Zurich Switzerland Control Systems group Department of Electrical Engineering Eindhoven University of Technology The Netherlands

ISBN: (纸本)9781479978878

We consider quasi-aggregative games for large populations of heterogeneous agents, whose interaction is determined by an underlying communication network. Specifically, each agent minimizes a quadratic cost function, which depends on its own strategy and on a convex combination of the strategies of its neighbors, and is subject to heterogeneous convex constraints. We suggest two distributed algorithms that can be implemented to steer the best responses of the rational agents to a Nash equilibrium configuration. The convergence of these schemes is guaranteed under different sufficient conditions depending on the matrices defining the agents' cost functions and on the communication network.

关键词： Games Aggregates Nash equilibrium Sociology Statistics Convergence Cost function

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Constrained linear quadratic deterministic mean field control: Decentralized convergence to Nash equilibria in large populations of heterogeneous agents

Constrained linear quadratic deterministic mean field contro...

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IEEE Annual Conference on Decision and control

作者： Sergio Grammatico Francesca Parise John Lygeros Control Systems group Department of Electrical Engineering Eindhoven University of Technology The Netherlands Automatic Control Laboratory ETH Zurich Switzerland

ISBN: (纸本)9781479978878

This paper considers the linear quadratic deterministic mean field control problem for large populations of heterogeneous agents, subject to convex state and input constraints, and coupled via a quadratic cost function which depends on the average population state. To control the optimal responses of the rational agents to a Nash equilibrium, we propose feedback iterative solutions based on operator theory arguments. Contrary to the state of the art, global convergence is ensured, under mild sufficient conditions on the matrices defining the cost functions, and not on the convex constraints.

关键词： Sociology Statistics Cost function Games Nash equilibrium Aggregates Convergence

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A shrinkage-based particle filter for tracking with correlated measurements

A shrinkage-based particle filter for tracking with correlat...

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Workshop on Sensor Data Fusion: Trends, Solutions, Applications (SDF)

作者： Aroland Kiring Naveed Salman Chao Liu Inaki Esnaola Lyudmila Mihaylova Department of Automatic Control and Systems Engineering University of Sheffield United Kingdom

This paper studies the problem of tracking with wireless sensor networks (WSNs) using received signal strength (RSS) measurements. The log-normal shadowing associated with RSS measurements from a mobile terminal is correlated both in space and time. We propose a particle filter that exploits the temporal and spatial correlation and estimates the covariance matrix of the measurement noise using the shrinkage technique. Simulation results show that using the estimated covariance matrix in the tracking filter improves considerably the filter performance. It is also demonstrated via simulations that the shrinkage-based particle filter exhibits superior performance to the particle filter without shrinkage when limited measurements are available. Results with high accuracy of tracking using the proposed method are presented.

关键词： Covariance matrices Sensors Time measurement Atmospheric measurements Particle measurements Correlation Noise measurement

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Model Predictive control approaches for Centrifugal Compression systems

Model Predictive Control approaches for Centrifugal Compress...

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IEEE Annual Conference on Decision and control

作者： Giampaolo Torrisi Sergio Grammatico Manfred Morari Roy S. Smith Automatic Control Laboratory ETH Zurich Switzerland Control Systems group Department of Electrical Engineering Eindhoven University of Technology The Netherlands

ISBN: (纸本)9781479978878

Model Predictive control (MPC) techniques are considered for industrial centrifugal compression systems with nonlinear dynamics. We consider the torque provided by an external drive and a recycle valve as control actuators for the system. Closed-loop stability in the presence of control constraints is studied via the contractive control Lyapunov function method. We solve the nonlinear MPC problem to assess a performance benchmark, and then design a Sequential Quadratic Programming (SQP) MPC approach which is computationally affordable. We show in several numerical simulations based on a realistic centrifugal compressor case study that the SQP MPC technique outperforms the classic linearized MPC and performs similarly to the nonlinear MPC approach.

关键词： Valves Recycling Mathematical model Predictive control Torque Surges Actuators

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Fuel efficiency improvement by optimal scheduling of diesel generators using PSO in offshore support vessel with DC power system architecture

Fuel efficiency improvement by optimal scheduling of diesel ...

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IEEE PES Asia-Pacific Power and Energy engineering Conference, APPEEC 2015

作者： Chauhan, Priyesh J. Rao, K. Srinivasa Panda, Sanjib K. Wilson, Gary Liu, Xiong Gupta, Amit Kumar Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore Electrical Power and Control Systems Rolls-Royce Singapore Pte. Ltd. Singapore Singapore

ISBN: (纸本)9781467381321

This paper presents optimal generation scheduling for minimization of fuel consumption (FC) in a typical offshore support vessel with DC power system architecture employing four identical diesel generator (DG) sets. FC is analyzed for (i) equal load sharing among DGs in AC architecture, (ii) equal load sharing among DGs in DC architecture and (iii) optimal load sharing among DGs in DC architecture using Particle Swarm Optimization (PSO). Due to the presence of non-linearity in Specific FC (SFC) curves of the diesel engines, the PSO algorithm is used. The SFC-vs-load relationship obtained from Brake SFC (BSFC) map of the diesel engines is characterized using a Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) interpolation. A solution to problem has been attained by comparing yearly fuel consumption in the three cases for the load profile of target vessel. This method can be applied to any vessel equipped with multiple generation units having DC power system architecture. © 2015 IEEE.

关键词： Scheduling

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Identifiability and Parameter Estimation of Linear Continuous-time systems under Irregular and Random Sampling

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IFAC-PapersOnLine 2015年第28期48卷 332-337页

作者： Mu, Biqiang Guo, Jin Wang, Le Yi Yin, George Xu, Lijian Zheng, Wei Xing Key Laboratory of Systems and Control Chinese Academy of Sciences Beijing100190 China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Department of Electrical and Computer Engineering Wayne State University DetroitMI48202 United States Department of Mathematics Wayne State University DetroitMI48202 United States Department of Electrical and Computer Engineering Technology Farmingdale State College State University of New York FarmingdaleNY11735 United States School of Computing Engineering and Mathematics University of Western Sydney PenrithNSW2751 Australia

This paper considers the problem of identifiability and parameter estimation of single-input-single-output, linear, time-invariant, stable, continuous-time systems under irregular and random sampling schemes. Conditions for system identifiability are established under inputs of exponential polynomial types and a tight bound on sampling density. Identification algorithms of Gauss-Newton iterative types are developed to generate convergent estimate sequences. When the sampled output is corrupted by observation noises, input design, sampling times, and convergent algorithms are intertwined. Persistent excitation (PE) conditions for strongly convergent algorithms are derived. Unlike the traditional identification, the PE conditions under irregular and random sampling involve both sampling times and input values. Under the given PE conditions, iterative and recursive algorithms are developed to estimate the original continuous-time system parameters. The corresponding convergence results are obtained. Several simulation examples are displayed to verify the theoretical results. © 2015

关键词： Continuous time systems Iterative methods Lyapunov methods Nonlinear control systems Parameter estimation Sampling convergence and asymptotical normality Estimation algorithm Identifiability Irregular sampling Linear continuous time system Non linear least squares

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On the behavior of first-order penalty methods for conic constrained convex programming when Lagrange multipliers do not exist

On the behavior of first-order penalty methods for conic con...

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IEEE Annual Conference on Decision and control

作者： Ion Necoara Andrei Patrascu Automatic Control and Systems Engineering Department University Politehnica Bucharest Romania

ISBN: (纸本)9781479978878

In this paper we analyze the numerical behavior of first-order quadratic penalty methods for solving large-scale conic constrained convex problems with composite objective function. Contrary to the most of the results on penalty methods, in this work we do not assume the existence of a finite optimal Lagrange multiplier. We derive the iteration complexity of the classical quadratic penalty method, where the corresponding penalty regularized formulation of the original problem is solved using Nesterov's fast gradient algorithm. We provide rate of convergence results in terms of feasibility violation and suboptimality for adaptive and non-adaptive variants of the penalty scheme, under various assumptions on the composite objective function. Finally, we show on a simple example that our complexity estimates are tight.

关键词： Linear programming Complexity theory Optimization Convergence Convex functions Programming Signal processing algorithms

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control of single axis magnetic levitation system using fuzzy logic control

Control of single axis magnetic levitation system using fuzz...

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Science and Information Conference (SAI)

作者： A. M. Benomair M. O. Tokhi Department of Automatic Control and Systems Engineering The University of Sheffield Sheffield UK

This paper presents an investigation into a system model for the stabilisation of a Magnetic Levitation System (Maglev's). The magnetic levitation system is a challenging nonlinear mechatronic system in which an electromagnetic force is required to suspend an object (metal sphere) in the air. The electromagnetic force is very sensitive to the noise which can create acceleration forces on the metal sphere, causing the sphere to move into the unbalanced region. Maglev's benefits the industry and the system has reduced power consumption, has increased power efficiency and reduced cost maintenance. The common applications for Maglev's Power Generation (e.g. wind turbine), Maglev's trains and Medical Device (e.g. Magnetically suspended Artificial Heart Pump). This paper presents comparative assessment of controllers for magnetic levitation dynamic response and robust characteristics of conventional PD and fuzzy PD. The main contribution of this paper is a robust fuzzy PD stabilisation scheme.

关键词： PD control Magnetic levitation Fuzzy logic Electromagnetic forces Steady-state Robustness

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ℋ∞ control problem for generalized discrete-time LTI systems

ℋ∞ control problem for generalized discrete-time LTI syste...

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American control Conference (ACC)

作者： Sebastian F. Tudor Cristian Oară The Department of Automatic Control and Systems Engineering Politehnica University of Bucharest Romania

We consider in this paper the suboptimal ℋ ∞ output feedback control problem for a generalized discrete-time LTI system, whose transfer function matrix is allowed to be improper or polynomial. The parametrization of all controllers that achieve closed-loop stability and guaranteed performance is given in a realization-based setting, involves two generalized Riccati equations, and features the same elegant simplicity of the standard (proper) case. A relevant numerical example proves the effectiveness of our approach.

关键词： Linear systems Polynomials Standards Output feedback Transfer functions Power system stability Riccati equations

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