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10th IFAC Symposium on Control of Power and Energy Systems (CPES)

作者： Umizaki, Mitsuhiro Uno, Fumichika Oozeki, Takashi Natl Inst Adv Ind Sci & Technol Tsukuba Ibaraki Japan

In order to optimize photovoltaic (PV) output curtailment control, forecasting a regional PV power generation are an important issue. Its estimation is also important as a basic step prior to forecasts. Upscaling algorithm is general approach for evaluating and forecasting a regional PV power generation because the number of monitored plants is usually limited. However, the method leads to large error when the characteristics of monitored plants differ from those of unknown plants in a region. In this paper, we analysed the errors on estimation and forecast of regional PV power generation with upscaling method by using monitoring data obtained from 2219 small PV plants in Kyushu, Japan. As the results, random sampling method has sufficient accuracy for day-ahead and short-term forecasts in case of the large number of reference plants, and unlike forecasts the minimum estimation error does not remain flat and continued to decrease as the number of power plants increased. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Photovoltaic Power control Optimization estimation algorithms Forecasts Machine learning

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To the Problem of Adaptive Guaranteed estimation

To the Problem of Adaptive Guaranteed Estimation

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17th IFAC Technical-Committee-on-Optimal-Control (TC 2.4) Workshop on Control Applications of Optimization (CAO)

作者： Khadanovich, Dina V. Shiryaev, Vladimir I. Natl Res Univ South Ural State Univ Dept Automat Control Syst Chelyabinsk Russia

The article deals with linear dynamical system state estimation problem under uncertainty when disturbance and measurement error statistics are unknown but the sets of their possible values are available. The approach to adaptive algorithm development of guaranteed estimation is proposed. The approach is based on the processing of innovation sequence values in the Kalman filter under conditions of a small number of available measurements. The Kalman filter implementation is performed for measurement data preprocessing the result of which is the mathematical model development and refining the estimates of unknown measurement errors. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Adaptive filters estimation algorithms Kalman filters Measurement noise Mathematical models Prediction

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Particle Gaussian mixture filters-II

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AUTOMATICA 2018年 98卷 341-349页

作者： Raihan, Dilshad Chakravorty, Suman Texas A&M Univ Dept Aerosp Engn College Stn TX 77840 USA

In our previous work, we proposed a particle Gaussian mixture (PGM-I) filter for nonlinear estimation. The PGM-I filter uses the transition kernel of the state Markov chain to sample from the propagated prior. It constructs a Gaussian mixture representation of the propagated prior density by clustering the samples. The measurement data are incorporated by updating individual mixture modes using the Kalman measurement update. However, the Kalman measurement update is inexact when the measurement function is nonlinear and leads to the restrictive assumption that the number of modes remains fixed during the measurement update. In this paper, we introduce an alternate PGM-II filter that employs parallelized Markov Chain Monte Carlo (MCMC) sampling to perform the measurement update. The PGM-II filter update is asymptotically exact and does not enforce any assumptions on the number of Gaussian modes. The PGM-II filter is employed in the estimation of two test case systems. The results indicate that the PGM-II filter is suitable for handling nonlinear/non-Gaussian measurement update. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： estimation algorithms Nonlinear filters Machine learning Gaussian mixture models Multimodality Markov chain Monte Carlo State estimation Curse of dimensionality Parallel algorithms

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Stability analysis of Extended, Cubature and Unscented Kalman Filters for estimating stiff continuous-discrete stochastic systems

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AUTOMATICA 2018年 90卷 91-97页

作者： Kulikov, Gennady Yu. Kulikova, Maria V. Univ Lisbon Inst Super Tecn CEMAT Ave Rovisco Pais 1 P-1049001 Lisbon Portugal

This paper studies stiffness and stability properties of Extended Cubature and Unscented Kalman Filters applied to continuous-discrete stochastic systems with stiff dynamic behavior. The main part of these methods relies on numerical integration of Moment Differential Equations (MDEs). Our focus is to understand how the stiffness of MDEs influences performance of the filters. The proposed linear stability analysis shows that the MDEs that have arisen within these methods can enlarge the stiffness of continuous-time stochastic model and, hence, require solvers with advanced stability properties for their effective and accurate treatment. Besides, the proposed nonlinear stability analysis proves that such MDEs may become extremely unstable in simulation intervals. The latter raises the uncertainty of state estimation and results in two interesting implications: (i) the lower-order Extended Kalman Filter outperforms the higher-order Cubature and Unscented Kalman Filters in the accuracy of state estimation of stochastic systems with unstable MDE behavior;(ii) the methods under exploration fail when the stiffness is large enough. Our theoretical consideration is supported by numerical tests with filters based on the MATLAB code ode15s, which is a benchmark solver for stiff ODEs. These are examined on linear and nonlinear stiff continuous-time stochastic models. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Stochastic systems estimation algorithms Kalman filters Nonlinear filters

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MMAE/LQR Yaw Control System of a Quadrotor for Constant Unknown Inertia *

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IFAC-PapersOnLine 2019年第12期52卷 170-175页

作者： Pedro Outeiro Carlos Cardeira Paulo Oliveira IDMEC Instituto Superior Técnico Universidade de Lisboa Portugal

This paper presents a methodology for angular control of a quadrotor that transports a constant unknown load, given the estimates on both inertia and angular velocity, based on measurements from an indoor multi-camera motion capture system and a gyroscope. The proposed control method is an LQR controller and the proposed estimation method is a Multi-Model Adaptive Estimator (MMAE). The control system obtained is validated both in simulation and experimentally, resorting to an off-the-shelf commercially available quadrotor.

关键词： Autonomous mobile robots estimation algorithms Parameter identification Sensor Fusion Embedded systems

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Multi-agent Localization of A Common Reference Coordinate Frame: An Extrinsic Approach

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IFAC-PapersOnLine 2019年第20期52卷 67-72页

作者： Quoc Van Tran Hyo-Sung Ahn School of Mechanical Engineering Gwangju Institute of Science and Technology Gwangju Republic of Korea

This paper studies the problem of multi-agent cooperative localization of a common reference coordinate frame in ℝ 3 . Each agent in a system maintains a body-fixed coordinate frame and its actual frame transformation (translation and rotation) from the global coordinate system is unknown. The mobile agents aim to determine their trajectories of rigid-body motions (or the frame transformations, i.e., rotations and translations) with respect to the global coordinate frame up to a common frame transformation by using local measurements and information exchanged with neighbors. We present two frame localization schemes which compute the rigid-body motions of the agents with asymptotic stability and finite-time stability properties, respectively. Under both localization laws, the estimates of the frame transformations of the agents converge to the actual frame transformations almost globally and up to an unknown constant transformation bias. Finally, simulation results are provided.

关键词： Multi-agent systems Frame Localization Distributed computation estimation algorithms Sensor networks Measurement instrumentation

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Identification of Heterogeneous Parameters in an Intracellular Reaction Network from Population Snapshot Measurements through Sensitivity Analysis and Neural Network

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IFAC-PapersOnLine 2019年第26期52卷 107-112页

作者： Dongheon Lee Arul Jayaraman Joseph S. Kwon Artie McFerrin Department of Chemical Engineering Texas A&M University College Station TX 77840 USA Texas A&M Energy Institute Texas A&M University College Station TX 77840 USA Department of Biomedical Engineering Texas A&M University College Station TX 77840 USA

Cells in a clonal cell-population exhibit a significant degree of heterogeneity in their responses to an external stimulus. In order to model a heterogeneous intracellular process, the individual-based population model (IBPM) has been developed in the past. Specifically, the IBPM approach can represent the heterogeneous dynamics in a cell population with a system of differential equations, whose model parameters follow probability density functions (PDF) instead of being constants. Therefore, in order to accurately predict the heterogeneous cellular dynamics, it is important to infer the PDFs of the model parameters from available experimental measurements. In this study, we propose a methodology to estimate the PDFs of the model parameters from population snapshot measurements obtained from flow cytometry. First, the PDFs of the model parameters are assumed to be normal so that a finite dimensional vector will be inferred from the measurements instead of inferring PDFs. Second, the sensitivity analysis is performed to identify which PDFs of the model parameters are identifiable and should be estimated from the available measurements. Next, in order to reduce the excessive number of evaluations of the IBPM during the PDF estimation process, an NNM is developed so that the output PDFs can be computed for given parameter PDFs. Lastly, the NNM is used to estimate the PDFs of the model parameters by minimizing the difference between the measured and predicted PDFs of the output. To show the effectiveness of the proposed methodology, the PDFs of parameters of a TNFα signaling model were estimated from in silico measurements.

关键词： estimation algorithms Stochastic systems Sensitivity analysis Identifiability

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Pitch Dynamics Analysis for an Agricultural Tractor with Image Processing Validation through an Off-Board Camera

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IFAC-PapersOnLine 2019年第5期52卷 492-497页

作者： L. Onesto M. Corno S. Savaresi Dipartimento di Elettronica Informazione e Bioingegneria Politecnico di Milano via G. Ponzio 34/5 20133 Milan Italy.

This work proposes an analysis of the pitch dynamics of a heavy-duty vehicle, namely an agricultural tractor. Considering maneuvers performed on a flat-asphalt surface, the analysis is performed through an image processing approach. The analysis focuses on the cabin displacement and on the vehicle body displacement. Moreover, the tires compression and the vehicle longitudinal slip are evaluated. The analysis shows how the cabin and the body displacements change in function of the vehicle longitudinal acceleration and how, due to the tires compression, the cabin and the body can oscillate, at the end of a braking maneuver. The results are used to evaluate the feasibility of a road gradient estimator based on the inertial measurement of a mono axial accelerometer installed in the cabin. In particular, the cabin displacement needs to be considered and an additional sensor which measures the cabin speed is required to avoid a drop of performance.

关键词： Vehicle dynamics Pitch estimation algorithms Kalman Filters Image Processing

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Estimating Edge-Local Triangle Count Heavy Hitters in Edge-Linear Time and Almost-Vertex-Linear Space

Estimating Edge-Local Triangle Count Heavy Hitters in Edge-L...

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IEEE High Performance Extreme Computing Conference (HPEC)

作者： Priest, Benjamin W. Pearce, Roger Sanders, Geoffrey Dartmouth Coll Thayer Sch Engn Hanover NH 03755 USA Lawrence Livermore Natl Lab Ctr Appl Sci Comp Livermore CA USA

ISBN: (纸本)9781538659892

We describe a methodology for estimating edge-local triangle counts using cardinality approximation sketches. While the approach does not guarantee relative error bounds, we will show that it preserves triangle count heavy hitters - the edges incident upon the largest number of triangles - well in practice. Furthermore, we provide empirical evidence that the sum of edge-local estimations yield reasonable estimates of the global triangle count for free. In this paper we describe a two-pass algorithm for estimating edge-local triangle count heavy hitters. The algorithm requires time linear in the number of edges, memory almost linear in the number of vertices, and is easy to parallelize. We provide results on dozens of real-world and synthetic graphs.

关键词： graphs triangle counting sublinear algorithms estimation algorithms

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Fixed Types of Motion in Aircraft Trajectory Recovering

Fixed Types of Motion in Aircraft Trajectory Recovering

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17th IFAC Technical-Committee-on-Optimal-Control (TC 2.4) Workshop on Control Applications of Optimization (CAO)

作者： Ivanov, Alexey G. Bedin, Dmitrii A. Fedotov, Andrey A. Ganebnyi, Sergey A. RAS UB Krasovskii Inst Math & Mech Ekaterinburg Russia New Informat Technol Aviat LLC St Petersburg Russia

We describe an algorithm for recovering a trajectory of an aircraft that is based on the construction of a bundle of approximating trajectories. Each of them is a possible version of the real aircraft motion. The specific feature of the algorithm is the approximation of measurements by means of a fixed set of motion patterns. A procedure of detecting the motion type determines the most probable motion pattern, and then the weight of the corresponding approximating trajectory in the final estimate of the aircraft current position increases. Such a design improves the accuracy of the coordinate determination at the stages of steady motion. The results of application of the algorithm to some model data are presented. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Target tracking Air traffic control Least-squares method Detection algorithms estimation algorithms Numerical methods Measurement noise Optimization

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