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5th IFAC International Symposium on Intelligent Components and Instruments for Control Applications

作者： Zimmerman, Y Brandes, A Oshman, Y Technion Israel Inst Technol Fac Mech Engn IL-32000 Haifa Israel

ISBN: (纸本)008044010X

A new decoding method is presented for linear analog encoders enabling major improvements in both accuracy and resolution. A simulation study is used to demonstrate the performance improvement of the proposed method, demonstrating that the new method can generate position estimates with accuracy about three times better than that of standard methods. Moreover, in some special cases, the resulting position accuracy can reach subnanometer levels, thus enabling further size reduction in the semiconductor industry. The proposed algorithm also yields velocity estimates better by about two orders of magnitude than those obtained with standard methods. Copyright (C) 2003 IFAC.

关键词： encoders Kalman filters estimation algorithms nonlinear filters accuracy measurement noise

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Ellipsoidal Estimates of Reachable Sets for Control Systems with Nonlinear Terms

Ellipsoidal Estimates of Reachable Sets for Control Systems ...

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20th World Congress of the International-Federation-of-Automatic-Control (IFAC)

作者： Filippova, Tatiana F. Russian Acad Sci Krasovskii Inst Math & Mech Ural Branch Sofia Kovalevskaya Str 16 Ekaterinburg 620990 Russia

The problem of estimating reachable sets of nonlinear dynamical control systems with quadratic nonlinearity and with uncertainty in initial states is studied. We assume that the uncertainty is of a set-membership kind when we know only the bounding set for unknown items and any additional statistical information on their behavior is not available. We present here approaches that allow finding ellipsoidal estimates of reachable sets which use the special structure of nonlinearity of studied control system. The algorithms of constructing such ellipsoidal set-valued estimates and numerical simulation results are given. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： estimation algorithms Nonlinear control systems Set-membership uncertainty Ellipsoidal calculus

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Piezo-actuated vibration disturbance mirror for investigating accelerometer-based tip-tilt reconstruction in large telescopes

Piezo-actuated vibration disturbance mirror for investigatin...

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7th IFAC Symposium on Mechatronic Systems (MECHATRONICS)

作者： Glueck, Martin Pott, Joerg-Uwe Sawodny, Oliver Univ Stuttgart Inst Syst Dynam ISYS Waldburystr 17-19 D-70563 Stuttgart Germany MPIA Konigstuhl 17 D-69117 Heidelberg Germany

The optical performance of large telescopes depends not only on the correction of atmospheric turbulences but also on the suppression of structural vibrations. Nowadays, these disturbances are compensated by Adaptive Optics (AO) systems. Especially for the vibration suppression new control concepts are developed. A well-known method is a state feedback controller. However, for observations with natural faint guide stars the integration time of the wavefront sensor is increased and therefore the bandwidth of the control loop is not sufficient for a fully vibration compensation. Hence, we want to avoid this problem by using an Accelerometer-based Disturbance Feedforward control (DFF), which is independent of the integration time. The vibrations are measured at the relevant telescope mirrors and the tip-tilt modes are reconstructed for the actuator control signals. For investigating the DFF a laboratory setup is built. The setup consists of a classical AO system and additional designed tip-tilt mirrors for simulating and compensating the vibrations. Several accelerometer are mounted at the disturbance mirror. Based on the measured accelerations two position estimators are investigated in order to use them in real telescope applications. (C) 2016, IFAC (International Federation of Automatic Control) Hosting Elsevier Ltd. All rights reseirved.

关键词： vibration measurement accelerometers signal reconstruction estimation algorithms actuators

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A FAST COMPUTATIONAL FRAMEWORK FOR LARGE-SCALE MOVING HORIZON estimation

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IFAC Proceedings Volumes 2007年第5期40卷 19-28页

作者： Victor M. Zavala Carl D. Laird Lorenz T. Biegler Chemical Engineering Department Carnegie Mellon University Pittsburgh PA USA 15213

Moving Horizon estimation (MHE) is an efficient optimization-based strategy for state estimation. Despite the attractiveness of this method, its application in industrial settings has been rather limited. This has been mainly due to the difficulty to solve, in real-time, the associated dynamic optimization problems. In this work, a fast MHE algorithm able to overcome this bottleneck is proposed. The framework exploits the advantages of simultaneous collocation- based formulations and makes use of large-scale nonlinear programming algorithms and sensitivity concepts. The approach is demonstrated on a full-scale polymer process, where accurate state estimates are obtained and on-line calculation times are reduced dramatically.

关键词： estimation algorithms real-time discretization finite elements nonlinear programming sensitivity analysis

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Timevarying Parameter Model estimation for Fermentation Process Using the EM-Algorithm

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IFAC Proceedings Volumes 2004年第3期37卷 127-132页

作者： Janne Paanajärvi Automation Technology Laboratory Helsinki University of Technology P.O.B 5400 FIN-02015 HUT FINLAND

Bioprocesses, like fed-batch fermentations, are complex, nonlinear and nonstationary systems. These qualities have led to use of adaptive models, which have simple, often linear, model structure but were the parameters vary in time. An important question then becomes what kind of adaptation strategy should be chosen. Here the parameter adaptation is formulated as a Kalman filtering problem. The required state-space model is estimated using the EM-algorithm

关键词： Parameter estimation Timevarying systems Fermentation processes Kalman filters estimation algorithms

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A Neural Network Approach for Robust Nonlinear Parameter estimation in Presence of Unknown-But-Bounded Errors

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IFAC Proceedings Volumes 2000年第16期33卷 317-322页

作者： Ivan Nunes da Silva Andre Nunes de Souza Mario Eduardo Bordon University of São Paulo - UNESP/FE/DEE School of Engineering Department of Electrical Engineering CP 473 CEP 17033-360 Bauru-SP Brazil

Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. This paper presents a novel approach to solve robust parameter estimation problems for nonlinear model with unknown-but-bounded errors and uncertainties. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the network convergence to the equilibrium points. A solution for the robust estimation problem with unknown-but-bounded error corresponds to an equilibrium point of the network. Simulation results are presented as an illustration of the proposed approach.

关键词： Parameter Identification Neural Networks Robust estimation Artificial Intelligence estimation algorithms

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Parameter estimation Versus System Structure

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IFAC Proceedings Volumes 1988年第1期21卷 81-85页

作者： B. Bona M. Maranzana Figini R. Foroni G. Rizzo G. Belforte Dipartimento di Automatica e Informatica Politecnico di Torino Torino Italy Centro di Teoria dei Sistemi CNR Dipartimento di Elettronica Politecnico di Milano Milano Italy Divisione Medicina Lavoro USLL 25 Verona Italy

Measurements are inevitably bound to experimental errors, whose probability distributions are generally unknown. When models of metabolic-endocrine systems or of drug kinetics are identified starting from noisy data, the question arises of how the parameters estimates are affected by the assumptions made. Aim of this work is to investigate whether and to what extent unreliable assumptions concerning the noise distribution influence the estimation process and to compare the efficiency of two estimation methods in the case of ‘ad hoc’ simulated data. Al though these are generated from two-compartment systems which can model some aspects of a β-blocking agent kinetics, both linear and nonlinear, it is believed that the findings of this study are of more general interest. The results show that the minimizing algorithms do not significantly differ as for their capability of fitting a bi-exponential curve to the simulated data. Evidence is given of the ambiguities encountered when hypotheses concerning the system structure are tested against the algorithms results. Most of the findings of this work can be expected from estimation theory; however they allow a better insight into the limits of applying estimation methods to biomedical problems, because the systems structure has been drawn from drug kinetics and a large variety of additive noise characteristics has been considered.

关键词： estimation algorithms data models non-compartmental analysis compartmental models noisy data

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Communication Constrained Distributed Spatial Field estimation Using Mobile Sensor Networks ⁎

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IFAC-PapersOnLine 2020年第2期53卷 9642-9649页

作者： Gennaro Notomista Magnus Egerstedt School of Mechanical engineering Institute for Robotics and Intelligent Machines Georgia Institute of Technology Atlanta GA30308 USA School of electrical and Computer engineering Institute for Robotics and Intelligent Machines Georgia Institute of Technology Atlanta GA 30308 USA

In this paper we address the problem of distributed estimation of spatial fields using mobile sensor networks with communication constraints. These constraints consist of a maximum communication bandwidth which limits the amount of data that can be exchanged between any two nodes of the network at each time instant. An algorithm to select the most significant data to be transferred between neighboring sensor nodes is developed starting from derived analytical error bounds. Moreover, the motion of the network nodes is controlled using a coverage control algorithm with the objective of minimizing the estimation uncertainty of each of the nodes. The resulting communication constrained distributed estimation algorithm is deployed on a team of ground mobile robots in the Robotarium, and its performance is evaluated both in terms of estimation accuracy of a simulated spatial field, and of the amount of data transferred.

关键词： Autonomous mobile robots Communication networks estimation algorithms Mobile robots Robotics

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RESPIRATION RATE estimation FOR MODEL PREDICTIVE CONTROL OF DISSOLVED OXYGEN IN WASTEWATER TREATMENT PLANT

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IFAC Proceedings Volumes 2007年第9期40卷 286-291页

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

Respiration rate is very important parameter for biological processes in wastewater treatment plant ( WWTP ). The sequential algorithm for estimate the respiration rate is proposed and investigated. The Kalman filter ... 详细信息

关键词： air biotechnology dynamic systems estimation algorithms estimation parameters Kalman filters modelling waste treatment

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STATIC AND DYNAMIC ATTITUDE DECOMPOSITION FOR estimation WITH MAGNETOMETER SENSOR

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IFAC Proceedings Volumes 2005年第1期38卷 168-173页

作者： Sebastien Changey Dominique Beauvois Volker Fleck Ecole Superieure d'Electricite Service Automatique 3 rue Joliot Curie 91192 Gif sur Yvette cedex France Institut Franco-Allemand de recherches de Saint-Louis 5 rue du General Cassagnou 68300 Saint-Louis France

A priori information given by the complete modelling of the ballistic behavior of a projectile is simplified to give a pertinent reduced evolution model. This model is composed of quasi-static and dynamic models. An extended Kalman filter is designed to estimate dynamic part of the 3 attitude angles (roll in [0, 2π], angle of attack and side-slip in the range of few milliradians) from measures of the magnetic field of the earth given by a three-axis magnetometer sensor embedded on the projectile. The algorithm has been tested in simulation, using realistic evolution of attitude data with measurement noise.

关键词： Kalman filters Attitude Magnetic fields Models estimation algorithms Nonlinear filters

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