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Fractional Order estimation Schemes for Fractional and Integer Order Systems with Constant and Variable Fractional Order Colored Noise

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2014年第12期33卷 3861-3882页

作者： Sierociuk, Dominik Ziubinski, Pawel Warsaw Univ Technol Inst Control & Ind Elect Warsaw Poland

The paper presents estimation schemes for discrete fractional and integer order state-space systems with fractional order colored noise. The fractional order colored noise is a generalization of the traditional colored noise (noise with dynamic dependency) for the case when the dynamics of noise is of fractional order. Proposed estimation algorithm additionally uses information about noise dynamics, which allows for obtaining better estimates of state vector. The numerical experiments of estimation integer order system with fractional noise are presented as well.

关键词： estimation algorithms Kalman filters Fractional order systems System noise Colored noise Variable order

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Identification of multi-sinusoidal signals with direct frequency estimation: An adaptive observer approach

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AUTOMATICA 2019年 99卷 338-345页

作者： Pin, Gilberto Wang, Yang Chen, Boli Parisini, Thomas Electrolux Italia SpA Porcia Italy Imperial Coll London Dept Elect & Elect Engn London England Univ Trieste Dept Engn & Architecture Trieste Italy Univ Cyprus KIOS Res & Innovat Ctr Excellence Nicosia Cyprus

This paper addresses the problem of estimating the frequencies, amplitudes and phases of then sinusoidal components of a possibly biased multi-sinusoidal signal. The proposed adaptive observer allows the direct adaptation of the frequency estimates with a relatively low dynamic order 3n + 1 (3n for an unbiased signal). The stability analysis proves the global exponential convergence of the estimation error and the robustness to additive norm-bounded measurement perturbations. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Sinusoidal signals Frequency estimation Adaptive systems estimation algorithms

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Computationally Efficient Pitch and Roll estimation Using a Unit Direction Vector

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2018年第2期67卷 459-465页

作者： Suh, Young Soo Univ Ulsan Dept Elect Engn Ulsan 44610 South Korea

This paper introduces a new attitude estimation algorithm for pitch and roll angles. Pitch and roll angles are represented by a unit vector, and its estimation error is estimated in the Kalman filter. The main theoretical contribution is that the error covariance equations are simplified to scalar equations. Thus, the proposed algorithm is computationally efficient. The proposed algorithm is also applied to vertical movement estimation. Simulation and experiment results show the effectiveness of the proposed method.

关键词： Attitude estimation algorithms inertial sensors Kalman filters orientation

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Online stiffness estimation for robotic tasks with force observers

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CONTROL ENGINEERING PRACTICE 2014年第1期24卷 92-105页

作者： Coutinho, F. Cortesao, R. Univ Coimbra Inst Syst & Robot P-3030290 Coimbra Portugal Coimbra Polytech Inst P-3030199 Coimbra Portugal

In this paper we propose an online stiffness estimation technique for robotic tasks based only on force data, therefore, not requiring contact position information. This allows estimations to be obtained in robotic tasks involving interactions with unstructured and unknown environments where geometrical data is unavailable or unreliable. Our technique - the Candidate Observer Based Algorithm (COBA) - uses two force observers, configured with different candidate stiffnesses, to estimate online the actual target object stiffness. COBA is embedded in a force control architecture with computed torque in the task space. The theoretical presentation of the algorithm, as well as simulation tests and experimental results with a lightweight robot arm are also presented. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Parameter estimation estimation algorithms Force control Observers Telemanipulation

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A Stochastic Computing Architecture for Iterative estimation

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2020年第3期67卷 580-584页

作者： Lunglmayr, Michael Wiesinger, Daniel Haselmayr, Werner Johannes Kepler Univ Linz Inst Signal Proc & Commun Engn A-4040 Linz Austria

Stochastic computing (SC) is a promising candidate for fault-tolerant computing in digital circuits. We present a novel stochastic computing estimation architecture allowing to solve a large group of estimation problems including least squares estimation as well as sparse estimation. This allows utilizing the high fault tolerance of stochastic computing for implementing estimation algorithms. The presented architecture is based on the recently proposed linearized-Bregman-based sparse Kaczmarz algorithm. To realize this architecture, we develop a shrink function in stochastic computing and analytically describe its error probability. We compare the stochastic computing architecture to a fixed-point binary implementation and present bit-true simulation results as well as synthesis results demonstrating the feasibility of the proposed architecture for practical implementation.

关键词： estimation Signal processing algorithms Computer architecture Approximation algorithms Stochastic processes Adders Fault tolerance Iterative algorithms stochastic computing estimation algorithms sparse estimation

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Theory of equivalence systems for describing algebraic closures of a generalized estimation model. II

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COMPUTATIONAL MATHEMATICS AND MATHEMATICAL PHYSICS 2011年第3期51卷 490-504页

作者： D'yakonov, A. G. Moscow MV Lomonosov State Univ Fac Computat Math & Cybernet Moscow 119991 Russia

Characteristic matrices and metrics of equivalence systems are studied that help give an efficient description of conjunctions of equivalence systems. Using these results, families of correct polynomials in the algebr... 详细信息

关键词： pattern recognition classification estimation algorithms algebraic approach algebraic closure algebra over algorithms correctness equivalence metric

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Evaluation of bias, precision, robustness and runtime for estimation methods in NONMEM 7

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JOURNAL OF PHARMACOKINETICS AND PHARMACODYNAMICS 2014年第3期41卷 223-238页

作者： Johansson, Asa M. Ueckert, Sebastian Plan, Elodie L. Hooker, Andrew C. Karlsson, Mats O. Uppsala Univ Pharmacometr Res Grp Dept Pharmaceut Biosci S-75124 Uppsala Sweden

NONMEM is the most widely used software for population pharmacokinetic (PK)-pharmacodynamic (PD) analyses. The latest version, NONMEM 7 (NM7), includes several sampling-based estimation methods in addition to the classical methods. In this study, performance of the estimation methods available in NM7 was investigated with respect to bias, precision, robustness and runtime for a diverse set of PD models. Simulations of 500 data sets from each PD model were reanalyzed with the available estimation methods to investigate bias and precision. Simulations of 100 data sets were used to investigate robustness by comparing final estimates obtained after estimations starting from the true parameter values and initial estimates randomly generated using the CHAIN feature in NM7. Average estimation time for each algorithm and each model was calculated from the runtimes reported by NM7. The method giving the lowest bias and highest precision across models was importance sampling, closely followed by FOCE/LAPLACE and stochastic approximation expectation-maximization. The methods relative robustness differed between models and no method showed clear superior performance. FOCE/LAPLACE was the method with the shortest runtime for all models, followed by iterative two-stage. The Bayesian Markov Chain Monte Carlo method, used in this study for point estimation, performed worst in all tested metrics.

关键词： Non-linear mixed effect models estimation algorithms FOCE Laplace SAEM Importance sampling

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A COMPARISON OF estimation METHODS FOR VECTOR AUTOREGRESSIVE MOVING-AVERAGE MODELS

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ECONOMETRIC REVIEWS 2012年第3期31卷 297-324页

作者： Kascha, Christian Univ Zurich Dept Econ CH-8032 Zurich Switzerland

Recently, there has been a renewed interest in modeling economic time series by vector autoregressive moving-average models. However, this class of models has been unpopular in practice because of estimation problems and the complexity of the identification stage. These disadvantages could have led to the dominant use of vector autoregressive models in macroeconomic research. In this article, several simple estimation methods for vector autoregressive moving-average models are compared among each other and with pure vector autoregressive modeling using ordinary least squares by means of a Monte Carlo study. Different evaluation criteria are used to judge the relative performances of the algorithms.

关键词： estimation algorithms Forecasting VARMA models

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Theory of Equivalence Systems for Describing the Algebraic Closures of a Generalized estimation Model

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COMPUTATIONAL MATHEMATICS AND MATHEMATICAL PHYSICS 2010年第2期50卷 369-381页

作者： D'yakonov, A. G. Moscow MV Lomonosov State Univ Fac Computat Math & Cybernet Moscow 119992 Russia

The recognition problem is considered in which the initial information is given by the values of similarity functions on pairs of objects. A generalization of the estimation algorithm model for this problem is proposed. A theory for the description and analysis of algebraic closures of the generalized and classical models is developed.

关键词： pattern recognition classification estimation algorithms algebraic approach algebraic closure algebra over algorithms correctness equivalence

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Effects of Differential Pressure Measurement Characteristics on Low Pressure-EGR estimation Error in SI-Engines

Effects of Differential Pressure Measurement Characteristics...

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8th IFAC Symposium on Advances in Automotive Control (AAC)

作者： Kiwan, Rani Stefanopoulou, Anna G. Martz, Jason Surnilla, Gopichandra Ali, Imtiaz Styles, Daniel Joseph Univ Michigan Ann Arbor MI 48109 USA Ford Motor Co Dearborn MI 48121 USA

With proper control, cooled LP-EGR can be used for knock mitigation in SI engines, enabling fuel economy improvements through snore optimal combustion phasing and lower fuel enrichment at high loads. In addition, it can allow more aggressive downsizing and boosting. Due to the inherent pressure pulsations and low differential pressures across the EGR valve, however, estimating;the LP-EGR within the inducted charge can be problematic. The accuracy of this estimation, based on a pressure differential (Delta P) tneasurerrient and the steady compressible flow orifice equation is investigated for various Delta P sensor response speeds and sampling rates using a GT-Power model of a modified Ford 1.6 L EcoBoost engine. In addition, an unsteady compressible flow orifice equation that accounts for flow inertia is derived and used to estimate LP-EGR. for the case of a fast response Delta P sensor. Errors in the estimated EGR percentage using the steady compressible orifice equation with averaged Delta P measurement can he as high as 30%, and errors within +/- 1% require a Delta P of at least 10 kPa. These two measures can be improved up to a maximum EGR estimation error of 10% and a minimum Delta P of 4 kPa respectively through the use of crank-angle resolved Delta P measurement. Further improvements are possible with the new unsteady orifice equation, where all errors are reduced roughly to within +/- 1%. the effect of inertia, however, can be mimicked in the steady orifice equation with a realistic sampling rate and a slower sensor with an appropriately selected response speed, resulting in a maximum error of 5% and errors within +/- 1% for Delta P exceeding 1 kPa. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Low pressure exhaust gas recirculation Differential pressure measurement Error analysis estimation algorithms Pulsating flow

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