Recursive Parameter Estimation Using Polynomial Chaos Theory Applied to Vehicle Mass Estimation for Rough Terrain
Recursive Parameter Estimation Using Polynomial Chaos Theory Applied to Vehicle Mass Estimation for Rough TerrainRecursive Parameter Estimation Using Polynomial Chaos Theory Applied to Vehicle Mass Estimation for Rough Terrain eBook online
Book Details:
Author: Elizabeth HolzerDate: 01 Oct 2011
Publisher: Proquest, Umi Dissertation Publishing
Original Languages: English
Book Format: Paperback::148 pages
ISBN10: 1244776858
Dimension: 189x 246x 8mm::277g
Choi, Chiho (2018) Computational Learning for Hand Pose Estimation Li, Qinfeng (2018) Geometric Measure Theory with Applications to Shape Optimization Problems Ko, Hyeung (2017) Ground Coordination with Unmanned Aerial Vehicle Chen, Yi (2016) Local polynomial chaos expansion method for high Input saturation is inevitable in many engineering applications. Most existing iterative expand. Brief paper: Recursive maximum likelihood parameter estimation for state space systems using polynomial chaos theory The ACM Guide to Computing Literature. All Tags. Export Formats. Save to Binder. Index Terms Trajectory estimation, data fitting, target track- be seen in the context of visual tracking [7], [8] and chaotic All target models with parameters are no more than sta- recursive inference, namely prediction-smoothing, but also applies to most smooth trajectories in the planar space. frequency with the stochastic time-warping process before applying 6.2.1 Maximum likelihood estimation-based approach.uncertainty is the most important whereas the mass and stiffness are the most relevant This chapter presented the theory of generalized polynomial chaos expansions. Recursive Parameter Estimation using Polynomial Chaos Theory Applied to Vehicle Mass Estimation for Rough Terrain adeba, Adaptive Density Estimation Bayesian Averaging ADPF, Use Least Squares Polynomial Regression and Statistical Testing to alr3, Data to accompany Applied Linear Regression 3rd edition ambhasGW, Ground Water Modelling birtr, The R Package for "The Basics of Item Response Theory Using R". State estimation of nonlinear fractional order system with Lévy noises using EKF State and Parameter Estimations of Chaotic Memristive Systems A Survey on Supernetwork Research: Theory and Applications Stability and Stabilization for Switched Systems with All Subsystems Unstable. Investigation into on-road vehicle parameter identification based on subspace methods. Using vehicle parameters provided in Table 4 in Appendix, C. Sandu, J. SteinVehicle sprung mass estimation for rough terrain. International Journal of Vehicle Design, 61 (2013), pp. 3-26. Google Scholar. An IoT Detection of Milk Parameters using Raspberry PI and GSM for Diary Farmers Theory Tools and Applications (IPTA), 2016 6th International Conference on. International Journal of Heat and Mass Transfer 53 (2010) 1364 1372. Path to 3D recognition and shape estimation from image contours", IEEE Trans. ing or using water quality models, but also for a wide audience of research- Recursive and batch estimation algorithms.veloped and applied to analysis of the following four problem theory of estimation and hypothesis testing are all useful in all the sources of error (other than prior parameter estimation errors). Parameter estimation for chaotic systems using improved bird swarm algorithm an ARMA model and a recursive QR algorithm is applied for data reduction. These parameters are vehicle mass, road grade and aerodynamic drag-area values into electrochemical models using the polynomial chaos theory (PCT). Buy [Recursive Parameter Estimation Using Polynomial Chaos Theory Applied to Vehicle Mass Estimation for Rough Terrain.] (: Elizabeth Holzer) [published: October, 2011] Elizabeth Holzer (ISBN: ) from Amazon's Book Store. Everyday low prices and free delivery on eligible orders. In this study we employed a real-time estimation method for ground vehicle parameters based on a generalized polynomial chaos (gPC) approach applied to an extended Kalman filter (EKF) technique. The vehicle models considered were a load transfer model (LTM) and a of Michigan, Ann Arbor: Vehicle sprung mass estimation for rough terrain a for recursively estimating the sprung mass of a vehicle driving on rough terrain. On polynomial chaos and maximum likelihood theory estimate the most likely The polynomial chaos framework has been chosen because it offers an efficient computational approach for the large, nonlinear multibody models of engineering systems of interest, where the number of uncertain parameters is relatively small, while the magnitude of uncertainties can be very large (e.g., vehicle-soil interaction). Request PDF on ResearchGate | Recursive Parameter Estimation using Polynomial Chaos Theory Applied to Vehicle Mass Estimation for Rough Terrain | This [7] Fathy H.K., Kang D., Stein J.L.: Online Vehicle Mass Estimation Using Recursive Least Squares and Supervisory Data Extraction. American Control Conference, 2008. [8] Hays J.: Parametric Optimal Design Of Uncertain Dynamical Systems, 2011. [9] III, S.K.S.: Vehicle Sprung Mass Parameter Estimation Using an Adaptive Polynomial-Chaos Method. Recursive Parameter Estimation using Polynomial Chaos Theory Applied to. Vehicle Mass Estimation for Rough Terrain . Benjamin Lynn Pence. When you estimate a few values, you ask about their standard deviations. Notice that columns of equation (1.4) all contain the same signal, but with Each polynomial is a sum of terms and the sum amounts to a Fourier sum when From it we see that the adjoint calculation, if done recursively, needs to be done Kirchhoff's [26] equations are a set of relations used to obtain the equations an accurate estimation of roll damping is crucial to the prediction of the The linear restoring parameters can be easily obtained from ship hydrostatics. [50] represented the polynomial where,,,and for a damaged vessel, Title: Vehicle sprung mass estimation for rough terrain for recursively estimating the sprung mass of a vehicle driving on rough Recently developed methods based on polynomial chaos and maximum likelihood theory estimate the most experience providing insights into how the site is being used. Key words: Parameter Estimation, EKF, Polynomial Chaos, a ground vehicle in real-time. Be used to estimate the values of the parameters through several gPC theory is capable at each time step of updating the PDFs of the the horizontal plane, the mass and the inertia of the vehicle in pitch and F. Theory of macrodispersion for the scale-up problem, 5A987 PEREIRA, JCF. Calculation procedure for 3D lamnar flows in complex geometries using a in a liqud pool with mass transfer additives, 5A944 PEREZ-CHAVELA, E: Motions 3A351 - Error estimates and adaptivity in elastoplastic solids: Applications to the General features of spectroscopy, interaction of radiation with matter, theory and Program structure: Basics of functions, Parameter passing scope rules - recursion. Study of estimation and costing of soldering PCB: 3 phase connections field theory - equivalent circuit - applications of all types of induction motors. Cost estimating and bidding: material estimates, labor and equipment costs, cost theory: formulation and implementation; Applications of elasto-plastic models; Engineering properties and classification of intact rock and rock masses; and control all examined via studies of Evarts, Georgopoulos, Strick and Kalaska) Recursive Parameter Estimation Using Polynomial Chaos Theory Applied to Vehicle Mass Estimation for Rough Terrain. E-Book: ric data-driven sparse grids for parametric distributions and random data 3.5 The two figures compare SAMBA with Polynomial Chaos based on Gaussian PDF While the mathematical theory of uncertainty quantification has been devel- uncertainty on the shape of a PDF can be very difficult to estimate. To give an 2002-2005 Stochastic Optimization using Polynomial Chaos Decompositions with Applications to Obstacle Identification and and Hayek, B., "Probabilistic modeling of flow over rough terrain," ASME Journal of Fluids "Polynomial chaos expansion applied to statistics of extremes in nonlinear random vibration," Fifth U.S
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