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A DUAL J -LOSSLESS FACTORISATIONS FOR SUBOPTIMAL H ∞ – estimation IN DELTA DOMAIN

IFAC Proceedings Volumes 2002年第1期35卷 31-36页

作者： Piotr Suchomski Technical University of Gdansk WETI-KSA Narutowicza 11/12 80-952 Gdansk Poland

The paper deals with a problem of numerical conditioning of basic J – lossless factori-sations associated with suboptimal H ∞ – norm estimation of discrete-time processes described in the so-called delta-domain. State space formulae for dual J – lossless factorisations of a chain scattering representation of the estimated process are given. Solutions are obtained via solving two coupled algebraic Riccati equations. A relative condition number of the delta-domain algebraic Riccati equation is employed as a measure of numerical conditioning of these solutions. A numerical example is given to show that solutions obtained for the delta operator are much better-conditioned than its counterpart versions based on the common forward shift operator.

关键词： estimation algorithms linear filters numerical algorithms Optimal estimation Riccati equations

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Adaptive Windowing Discrete-Time Velocity estimation Techniques: Application to HAPTIC Interfaces

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IFAC Proceedings Volumes 1997年第20期30卷 445-451页

作者： Vincent Hayward Farrokh Janabi-Sharifi Chung-Shin Jason Chen Department of Electrical Engineering and Center for Intelligent Machines McGill University 3480 University Street Montréal PQ Canada H3A 2A7 http://www.cim.mcgill.ca/~hayward/Home.html

A method is described to estimate velocity from discrete and quantized position samples via adaptive windowing. It addresses the shortcomings of previously known methods which necessitate tradeoffs between noise reduction, control delay, estimate accuracy, reliability, computational load, transient preservation, and which cause difficulties with tuning. The method is optimal in the sense that it minimizes the velocity error variance while maximizes the accuracy of the estimates. The design of the estimator requires the selection of only one parameter, namely a bound on the noise. Simulation and experimental results are presented.

关键词： Adaptive digital filters Discrete time Closed loop control Computer interfaces estimation algorithms PD controllers Nonlinear filters Velocity Measurements

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Parameter estimation of two classes of nonlinear systems with non-separable nonlinear parameterizations☆

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AUTOMATICA 2024年 163卷

作者： Ortega, Romeo Bobtsov, Alexey Nikolaev, Nikolay Costa-Castello, Ramon ITAM Dept Elect & Elect Engn Mexico City Mexico Hangzhou Dianzi Univ Sch Automat Hangzhou 310005 Zhejiang Peoples R China ITMO Univ Dept Control Syst & Robot Kronverkskiy Ave 49 St Petersburg 197101 Russia IPME Lab Control Complex Syst VO Bolshoj Pr 61 St Petersburg 199178 Russia Univ Politecn Catalunya UPC Catalonia Barcelona Spain

In this paper we address the challenging problem of designing globally convergent estimators for the parameters of nonlinear systems containing an exponential function whose power depends on unknown parameters. This class of non-separable nonlinearities appears in many practical applications, and none of the existing parameter estimators is able to deal with them in an efficient way. Our main technical contribution is the development of a lifting procedure for non-separable nonlinearly parameterized regressor equations to obtain separable ones, to which we can apply a recently reported estimation procedure. This is illustrated with a human musculoskeletal dynamics problem. The procedure does not assume that the parameters leave in known compact sets, that the nonlinearities satisfy some Lipschitzian properties, nor rely on injection of high-gain or the use of complex, computationally demanding methodologies. Instead, we propose to design a classical on-line estimator whose dynamics is described by an ordinary differential equation given in a compact precise form. (c) 2024 Elsevier Ltd. All rights reserved.

关键词： Nonlinear systems Observers estimation algorithms Regression estimates Excitation

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Non-parametric frequency response estimation using a local rational model 1

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IFAC Proceedings Volumes 2012年第16期45卷 49-54页

作者： Tomas McKelvey Guillaume Guérin Dept. of Signals and Systems Chalmers University of Technology SE-412 96 Gothenburg Sweden ENSEIRB-MATMECA Université de Bordeaux France

A review of the relationship between the frequency response function of linear system and the DFT of the input and output signals show that the output DFT is a sum of two terms. The first term contain the FRF multiplied with the input DFT and the second term capture the effect when the system is not operating in a periodic fashion. The utilization of these two terms when performing non-parametric frequency response function estimation has led to the previously developed Local Polynomial Method. This paper acknowledge that the two terms can better be approximated by local rational functions with a common denominator polynomial and a new method called Local Rational Method has been developed. Numerical simulations illustrate the performance of the new rational method in comparison with the polynomial one. The results suggest that the new rational method gives better performance when the system has a resonant behavior.

关键词： system identification discrete Fourier transform frequency response estimation local models estimation algorithms

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Fast Size Distribution estimation of Crushed Rock Aggregate using Laserprofilometry

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IFAC Proceedings Volumes 2011年第1期44卷 12132-12137页

作者： A. Taskinen M. Vilkko P. Itävuo A. Jaatinen Department of Automation Science and Engineering Tampere University of Technology Finland P.O. Box 692 FIN-33101 Energy & Process Systems Metso Automation Finland P.O. Box 237 FIN-33101

Abstract This paper introduces an algorithm for the estimation of size distribution of crushed aggregate based on 3D-image of a moving conveyor belt obtained by a laser profilometer. The aim of the study is to obtain measurement information that can be utilized mainly for the automatic control of crushers. Preferably the computation should be done in real-time, i.e. faster than the velocity of the conveyor belt. This sets demanding requirements on the computational efficiency of the algorithm. The computation speed is the primary criterion for the algorithm developed and successful results of that development are presented in this paper.

关键词： Size distribution estimation algorithms Laserprofilometry 3D measurement Crushed aggregate Granular material

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Bayesian Fill Volume estimation Based on Point Level Sensor Signals ⁎

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IFAC-PapersOnLine 2020年第2期53卷 1261-1267页

作者： Johannes Zumsande Karl-Philipp Kortmann Mark Wielitzka Tobias Ortmaier Institute of Mechatronic Systems Leibniz University Hannover Germany

In dry bulk and fluid processing, the composites are usually stored in hoppers, tanks, or other containers. Due to the economic advantages, binary point level sensors, which detect fill level exceeding, are widely used for process monitoring and control. In this paper, we propose different filters for estimating the probability distribution of the fill volume based on a time-variant measurement distribution and a stochastic physical model with white process noise. A filter based on the model prediction with separated measurement update and two Bayesian particle filters are proposed and compared with a simulated ground truth. The performance measures are the root-mean-square error, the precision of the 95 % and 75 % credible intervals, and the average value of the estimated probability density function at the simulated fill volumes.

关键词： Bayesian filter data fusion probabilistic models stochastic approximation estimation algorithms

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Joint Maximum a Posteriori Smoother for State and Parameter estimation in Nonlinear Dynamical Systems *

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IFAC Proceedings Volumes 2012年第16期45卷 900-905页

作者： Dimas A. Dutra Bruno O.S. Teixeira Luis A. Aguirre Programa de Pós-Graduação em Engenharia Elétrica - Universidade Federal de Minas Gerais - Av. Antônio Carlos 6627 31270-901 Belo Horizonte MG Brasil Departamento de Engenharia Eletrônica - Universidade Federal de Minas Gerais

In this paper, we propose and demonstrate the direct use of optimization to search for the mode of the joint posterior state distribution of stochastic nonlinear dynamical systems. That is accomplished by forming a very large but sparse nonlinear optimization problem with the states in all time instants as decision variables. The proposed method generalizes well for parameter estimation without the need for treating them as augmented states and the introduction of artificial dynamics. It is also possible to estimate parameters such as the noise variances, which are assumed known in traditional methods.

关键词： estimation algorithms Parameter estimation Stochastic modelling System identification System state estimation

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Duality Between Point-Mass and Simulation Approaches to State estimation

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IFAC Proceedings Volumes 2000年第13期33卷 113-118页

作者： Miroslav Šimandl Ondřej Straka Jakub Královec Department of Cybernetics and Center for Research of Cybernetic Systems Faculty of Applied Sciences University of West Bohemia Univerzitní 8 306 14 Plzeň Czech Republic

Two significant approaches, point-mass approach and Monte Carlo simulation approach, for an approximation of Bayesian recursive relations representing the general solution of the nonlinear state estimation problem are discussed. The stress is laid on finding their real fundamentals and common features. Both approaches use special types of grids substituting the continuous state space. However, the construction of the grids and the way of storing information about conditional probability density functions of the state are based on different ideas. Although the approaches are seemingly different, it is shown that there is a duality between them. In addition to the duality, an analysis of these nonlinear filter design techniques points out some common aspects and problems to be solved.

关键词： stochastic systems nonlinear systems nonlinear filters probability density function estimation algorithms Monte Carlo simulation

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A New Strategy of Non-Linear Trajectory Generation for a Platoon to Reduce Inter-Vehicle Error Distance estimation

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IFAC Proceedings Volumes 2004年第22期37卷 721-726页

作者： AbdelBaset Moh'd Hasan Awawdeh Felipe Espinosa Electronics Department. Polytechnics School. University of Alcalá. Spain.

This work is focused on estimating the distance error between vehicles of a platoon. This error is especially serious in non-linear trajectories and it gives place to lateral and longitudinal oscillations in the platoon guidance. For this reason, a new strategy is presented in which the leader, divides the trajectory into sub-trajectories as a function of the curvature and generates a set of points separated by a sampling-distance which is calculated as a function of the curvature in order to limit the inter-vehicle spacing error. This set of points is considered as the reference trajectory, which all the other vehicles have to follow.

关键词： Point-to-point control Trajectory Planning estimation algorithms Set-point control algorithms Spline Path planning curves Automated guided vehicles Autonomous vehicles Error analysis

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THE HYBRID estimation ALGORITHM FOR WASTEWATER TREATMENT PLANT ROBUST MODEL PREDICTIVE CONTROL PURPOSES AT MEDIUM TIME SCALE

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IFAC Proceedings Volumes 2007年第9期40卷 280-285页

作者： T. Rutkowski M.A. Brdys Faculty of Electrical and Control Engineering Gdansk University of Technology ul. G. Narutowicza 11/12 80 952 Gdansk Poland School of Engineering Department of Electronic Electrical and Computer Engineering The University of Birmingham Birmingham B15 2TT UK

The paper proposes an approach to designing the hybrid estimation algorithm/module (HEA) with moving measurements window for Wastewater Treatment Plant (WWTP) Robust Model Predictive Control (RMPC) purposes at medium time scale. The RMPC uses a dedicated grey-box model of biological reactor for the system outputs prediction purposes. The grey-box model parameters are dependant on the plant operating point. Hence, these parameters and grey-box model state should be estimated according to the current operating plant condition. The needed parameters and state estimates at medium time scale are provided by the HEA algorithm. The HEA consist of the set-bounded parameter and state estimation algorithm cooperated with the Extended Kalman Filter (EKF) algorithm. The HEA algorithm is used to ensure robustness of grey-box model parameter and state estimates in situation of limited amount of hard measurements on the WWTP. The state estimates provided by the EKF are used as pseudo measurements of the states and the set-bounded estimation algorithm produce sets bounding the grey-box model parameters and states. There are two hybrid estimation algorithms presented and described in the paper: algorithm of explicit method and algorithm of implicit method. Both hybrid estimation algorithms are validated by simulation base on real data records and calibrated model of Kartuzy WWTP in northern Poland.

关键词： biotechnology hierarchical control systems model predictive control robust control estimation algorithms bounding method uncertainty

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