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A finite-difference method for linearization in nonlinear estimation algorithms (Reprinted from Automatica, vol 33, pg 2053-2058, 1997)

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MODELING IDENTIFICATION AND CONTROL 1998年第3期19卷 141-152页

作者： Schei, TS SINTEF N-7034 Trondheim Norway

Linearizations of nonlinear functions that are based on Jacobian matrices often cannot be applied in practical applications of nonlinear estimation techniques. An alternative linearization method is presented in this paper. The method assumes that covariance matrices are determined on a square root factored form. A factorization of the output covariance from a nonlinear vector function is directly determined by "perturbing" the nonlinear function with the columns of the factored input covariance, without explicitly calculating the linearization and with no differentiations involved. The output covariance is more accurate than that obtained with the ordinary Jacobian linearization method. It also has an advantage that Jacobian matrices do not have to be derived symbolically.

关键词： covariance matrices estimation algorithms extended Kalman filters factorization methods nonlinear fibers Jacobian matrices linearization parameter estimation recursive estimation state estimation

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Bearings-Only Target Tracking via Partitioning estimation algorithms

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IFAC Proceedings Volumes 1982年第4期15卷 1659-1664页

作者： V. Petridis Department of Electrical Engineering Polytechnic School University of Thessalonika Greece

The bearings-only estimation of target velocity and position has been reformulated and treated as a combined estimation and identification problem which has been tackled through partitioning. Certain advantages of the partition estimation algorithm have been exploited to improve convergence. Here a different numerical realization which reduces the amount of computation is presented. Simulation examples are given.

关键词： Target tracking identification estimation algorithms

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State‐space stochastic volatility models: A review of estimation algorithms

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Applied Stochastic Models in Business and Industry 1996年第4期12卷

作者： Enrico Capobianco Department of Statistical Sciences University of Padua Italy

Stochastic volatility models (SVMs) represent an important framework for the analysis of financial time series data, together with ARCH‐type models; but unlike the latter, the former, at least from the statistical point of view, cannot rely on the possibility of obtaining exact inference, in particular with regard to maximum likelihood estimates for the parameters of interest. For SVMs, usually only approximate results can be obtained, unless particularly sophisticated estimation strategies like exact non‐gaussian filtering methods or simulation techniques are employed. In this paper we review SVM and present a new characterization for them, called ‘generalized bilinear stochastic volatility’. © 1996 John Wiley & Sons, Ltd.

关键词： stochastic volatility linear and nonlinear state space representation simulation techniques generalized bilinear stochastic volatility processes estimation algorithms

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Adaptive Algorithm for Fast 3D Characterization of Magnetic Sensors

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SENSORS 2025年第4期25卷 995-995页

作者： Boueke, Moritz Hoffmann, Johannes Ellrichmann, Mark Bergholz, Robert Schmidt, Gerhard Univ Kiel Fac Engn Dept Elect & Informat Engn D-24143 Kiel Germany Univ Kiel Univ Hosp Schleswig Holstein Dept Internal Med 1 Campus Kiel D-24105 Kiel Germany Univ Kiel Univ Hosp Schleswig Holstein Dept Pediat Surg Campus Kiel D-24105 Kiel Germany

Magnetic sensors are highly relevant in clinical and industrial applications such as localization tasks and geological investigations. The spatial behavior of these sensors is of great interest for accurate forward modeling and the consequential possibilities for sophisticated applications, e.g., solutions to inverse problems. In this contribution, we present a novel characterization approach using adaptive system identification approaches. We utilize a gradient-based algorithm for estimating impulse and corresponding frequency responses for a directivity analysis in 1D, 2D, and 3D. For this, we built a triaxial Helmholtz coil setup to generate a 3D directive field. This is controlled by an algorithm that exploits similarities in sensor behavior with respect to small differences in excitation field angles. We found advantages for a controlled adaptation, with faster convergence and a smaller system distance between estimations and measurements with a proposed control based on the contraction-expansion approach (CEA). With runtimes averaging less than 1.5 s per direction for full impulse response estimation, this proof of concept shows the potential of the proposed algorithm for enabling a feasible frequency and directivity characterization method.

关键词： magnetic sensor characterization estimation algorithms adaptive filters NLMS control magnetic field steering impulse response frequency response directivity

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On the use of constraints in least squares estimation and control

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AUTOMATICA 2002年第7期38卷 1113-1123页

作者： Robertson, DG Lee, JH Georgia Inst Technol Sch Chem Engn Atlanta GA 30332 USA Aspen Technol Global Solut Div Houston TX 77077 USA

In this article, we examine the effect of constraints on estimation and control methods based on quadratic penalty functions. We begin with estimation theory and analyze how constraints alter the statistical properties of the least squares estimates. It is shown that constraints can be used to formulate maximum likelihood (MLE) and maximum a posteriori (MAP) estimators for a variety of unimodal distributions. This provides greater flexibility over the assumption of normality inherent in the MLE and MAP interpretation of traditional least squares. We discuss how these ideas apply to state space models of dynamic systems. Possible applications for controllers that handle constraints are also discussed. A parameter estimation example is given to demonstrate the potential for improved performance over unconstrained least squares. (C) 2002 Elsevier Science Ltd. All rights reserved.

关键词： optimal estimation non-Gaussian processes constrained parameters estimation algorithms quadratic programming maximum likelihood estimators

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An adaptive strategy for Li-ion battery internal state estimation

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CONTROL ENGINEERING PRACTICE 2013年第12期21卷 1851-1859页

作者： Di Domenico, Domenico Prada, Eric Creff, Yann IFP Energies Nouvelles F-69360 Solaize France

Further developing a study presented in Di Domenico, Prada, and Creff (2011), this paper presents an extended Kalman filter (EKF) based on an electro-thermal model for the estimation of the internal state of a lithium-ion battery, i.e. state of charge and the cell overpotential. In order to compensate for uncertainties in the model parameters and in the measurements, it is first shown that the filter robustness strongly depends on the State of Charge (SOC) range. Then the filter weights are adapted according to the estimated SOC value. This estimation technique is tested using experimental data collected from a commercial A123 Systems lithium iron phosphate/graphite (LiFePO4/graphite) cell. The filter shows good performance. The estimation of SOC exhibits an average error within 3% range and the overpotential is estimated with a precision higher than 5 mV. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Kalman filters estimation algorithms Nonlinear models Observability Statistical analysis

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estimation and control strategies for a lipase production process

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CONTROL ENGINEERING PRACTICE 1996年第11期4卷 1521-1534页

作者： Charbonnier, S Cheruy, A Laboratoire d'Automatique de Grenoble ENSIEG/INPG BP 46 38402 St Martin d'Hères France

This paper deals with the design of a control system for a lipase production process. The aim is to maximise the enzyme production when the process is operating in fed-batch mode, by controlling the substrate feeding rate and by using the only on-line measurement available, C.E.R., given by gas analysis. At first, a dedicated estimation strategy is proposed to cope with the lack of on-line measurements. This strategy is based on minimal use of the complex and nonlinear process model in which kinetic parameters are hot perfectly known. It consists in splitting the estimation problem into three cascade subproblems and solving them by appropriate algorithms for which stability and convergence are proved under realistic conditions. The whole estimation (three state variables and two kinetic parameters) is tested and tuned by simulation and then successfully applied and validated on the real process. In the second part, an analysis of the process model is carried out to define the best operating conditions for maximised production. Then, a nonlinear controller is developed to maintain the process under these efficient operating conditions (ratio substrate/biomass kept constant). It is implemented on the process by coupling it with the previous estimation algorithm. The whole system is tested in simulation under realistic. conditions. It can be shown that it clearly increases lipase production and ensures process reliability, as the process becomes insensitive to disturbances.

关键词： biotechnology estimation algorithms nonlinear control adaptive control

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Experimental validation of direction of arrival estimation for high chirp-rate linear frequency modulated radar signals

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IET RADAR SONAR AND NAVIGATION 2021年第6期15卷 627-640页

作者： Mulinde, Ronald Attygalle, Manik Aziz, Syed Mahfuzul Univ South Australia UniSA STEM Mawson Lakes SA 5095 Australia Def Sci & Technol Grp Cyber & Elect Warfare Div Adelaide SA Australia

Direction of arrival (DOA) estimation for signals with large time-bandwidth products is very important in modern communication and radar systems. Traditional narrowband DOA estimation algorithms are not accurate for such wideband signals. Further complexities arise with non-stationary signals, for example, high chirp-rate linear frequency modulated (LFM). These complexities imply that achieving real-time performance with good DOA estimation accuracy is a challenge. This article uses experimentally acquired data on high chirp-rate LFM signals to validate a channelised version of MUltiple SIgnal Classification (MUSIC) for DOA estimation. This technique eliminates pre-processing and incoherently combines spatial pseudospectra from individual frequency channels to obtain a single accurate estimate and has much less computational complexity compared to coherent techniques. LFM signals of up to 500 MHz bandwidth and chirp rates of up to 50 MHz/mu s have been used in the investigations and results show accurate DOA estimation at low SNR (0 dB). This technique is suitable for even wider operational bandwidths and low latency implementations. To the best of our knowledge, this is the first time DOA estimation for such high chirp-rate LFM signals has been validated using real experimental data which is also corroborated with validation using synthetic data.

关键词： single accurate estimate individual frequency channels estimation algorithms Signal processing and detection experimental validation arrival estimation Radar equipment, systems and applications nonstationary signals wideband signals modern communication chirp-rate LFM signals time-bandwidth products chirp-rate linear frequency good DOA estimation accuracy frequency modulation radar systems experimentally acquired data radar signals bandwidth 500.0 MHz MUltiple SIgnal Classification array signal processing accurate DOA estimation chirp rates Interpolation and function approximation (numerical analysis) FM radar loss 0.0 dB direction-of-arrival estimation signal classification

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New algorithm for joint estimation of DOA and polarisation based on electrically large and complete electromagnetic vector sensor

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IET RADAR SONAR AND NAVIGATION 2020年第9期14卷 1279-1286页

作者： Zhu, Dongchen Chen, Baixiao Yang, Minglei Dong, Mei Xidian Univ Natl Lab Rader Signal Proc Xian 710071 Peoples R China

With the development of estimation algorithms for polarisation sensitive array (PSA) parameters, research has been focused on complete/incomplete electromagnetic vector sensor (EMVS) that is mainly based on electrically 'short' dipoles and/or electrically 'small' circular loops. Recently, electrically 'long' dipoles and electrically 'large' circular loops are further preferred and have been proposed to utilise more efficiently radiation characteristics. However, almost all available such EMVSs are only composed of either long dipoles or large circular loops. To sufficiently utilise relevant electromagnetic information, in this study an electrically 'large' EMVS is proposed, which is composed of a triad of long dipoles and a triad of large circular loops, co-located, and orthogonally oriented. With formulated array manifold of the proposed EMVS, a close-form algorithm is developed to estimate an incident source's azimuth-elevation direction-of-arrival (DOA) and polarisation simultaneously without prior knowledge, and verified that its estimation accuracy is closely approaching corresponding to Cramer-Rao Bound. It is demonstrated that when with inaccurate prior knowledge, the proposed algorithm has better performance than existing algorithms that were designed for the incomplete EMVS with either long dipoles or large loops. Finally, simulation results also show that with increased electrical size of the EMVS, the estimation accuracy is significantly improved.

关键词： direction-of-arrival estimation electromagnetic devices sensor arrays electric sensing devices magnetic sensors magnetic field measurement electric field measurement electrically large vector sensor estimation algorithms polarisation sensitive array parameters electrically long dipoles electrically large circular loops relevant electromagnetic information electrically large EMVS formulated array manifold close-form algorithm DOA estimation complete-incomplete electromagnetic vector sensor radiation characteristics azimuth-elevation direction-of-arrival estimation Cramer-Rao bound

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Inferential estimation of viscosity index on a lubricant production plant

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CONTROL ENGINEERING PRACTICE 1996年第12期4卷 1659-1667页

作者： Mitchell, A Willis, MJ Tham, MT Bitar, SS MOBIL OIL CO LTD STANFORD HOPE SS17 9LLESSEXENGLAND

This paper presents an industrial case study examining the application of inferential estimation to a lubricant production plant. Three estimation algorithms are studied, First, an existing plant inference model is compared to a static estimator designed using information obtained from plant experiments. Next, the case for a dynamic and adaptive algorithm is presented, The procedures required to initialise the adaptive estimator are described, and implementation issues are discussed. This paper demonstrates that (provided such issues are carefully considered) an adaptive inferential measurement algorithm may be used to provide timely and accurate inferences.

关键词： chemical industry estimation algorithms inference statistical analysis

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