The Innovations Approach to Experimental Modeling of Flexible Structures

1998 ◽  
Vol 120 (3) ◽  
pp. 689-694 ◽  
Author(s):  
R. Kashani
Keyword(s):  
Flexible Structures ◽  
Least Square ◽  
Experimental Modeling ◽  
Model Structure ◽  
Flexible Plate ◽  
Unknown Parameters ◽  
Space Modeling ◽  
Linear Least Square ◽  
Two Sides ◽  
Selection Of

A technique based on the innovations approach to linear least square identification is proposed for experimental state space modeling of flexible structures. Upon the selection of the model structure and order, the unknown parameters are identified by minimizing the sum of squares of the innovations process. Contrary to having a black-box approach to experimental modeling, this technique uses physical parameterization of the structural dynamics, as well as measurement noise properties. The innovations approach to experimental modeling of the flexible structures automates the identification of unknown parameters in the model and reduces the number of these unknowns to its minimum resulting in small variances in their estimated values. The effectiveness of this experimental modeling technique is demonstrated by accurately identifying the modal information of a rectangular flexible plate, free at two sides and fixed at the other two. The plate is patched with PZT actuators and nearly-collocated sensors at two locations.

Optimisation of Autonomous Threaded Fastenings Based on Non-Linear Least Square Method With GUIs

2004 ◽  
Author(s):  
Mongkorn Klingajay ◽  
Wuttipong Wanathap
Keyword(s):  
User Interfaces ◽  
Least Square Method ◽  
Estimation Procedure ◽  
Least Square ◽  
Unknown Parameters ◽  
Screw Insertion ◽  
Assembly Method ◽  
Non Linear ◽  
On Line ◽  
Linear Least Square

Threaded fastenings are a common assembly method, accounting for over a quarter of all assembly operations. They are especially popular because they permit easy disassembly for maintenance, repair, relocation and recycling. Screw insertions are typically carried out manually as it is a difficult operation to automate. There is very little published research on automating threaded fastenings, and most research on automated assembly focuses on the peg-in-hole assembly problem. Non-linear least square method was designed and employed to identify torque signature signals during online threaded fastening. Creating interactive simulations and graphical user interfaces became necessary as a visualization aid. This provides help and support for the user, allowing them to concentrate on the concept they are illustrating and to put emphasis on the monitoring process rather than the mechanics of running the program. This paper presents a Graphical User Interface (GUI) tool to accommodate and support threaded fastening operations used in assembly line industries. This tool was produced as interactive software with a convenient GUI in combination with the computing and graphics capability of MATLAB. It has applied to automated monitoring of threaded fastenings based-on an analytical model and on-line parameter estimation. The monitoring problem deals with predicting the integrity of the screw insertion process based on the torque vs. insertion angle curves generated during the insertions. A Non-linear Least Square Method (NLSM) is applied for estimation of four unknown parameters during a self-tapping screw insertion to be presented. It is shown that these parameters, required by the model, can be reliably estimated on-line. Experimental results are presented to validate the estimation procedure.

The application of iterative optimization techniques to chemical kinetic data of large random error

1976 ◽  
Vol 54 (21) ◽  
pp. 3330-3341 ◽  
Author(s):  
George H. Schmid ◽  
Valeria M. Csizmadia ◽  
Paul G. Mezey ◽  
Imre G. Csizmadia
Keyword(s):  
Kinetic Data ◽  
Chemical Kinetic ◽  
Optimization Techniques ◽  
Least Square ◽  
Least Square Fit ◽  
Simple Scaling ◽  
Data Points ◽  
Linear Least Square ◽  
Selection Of ◽  
Chemical Rate

The possibilities of improving the computational processing of chemical rate measurements, in the frame of linear and non-linear least-square fit methods, are investigated. A simple scaling technique to avoid the distortion of the fitted parameters, inherent in the logarithmic transformation of the rate equation, is tested on several examples, and an iterative discarding method for the selection of accurate data points is recommended.

scholarly journals Nonlinear State Space Modeling and System Identification for Electrohydraulic Control

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Jun Yan ◽  
Bo Li ◽  
Hai-Feng Ling ◽  
Hai-Song Chen ◽  
Mei-Jun Zhang
Keyword(s):  
State Space ◽  
Linear Time ◽  
Least Square ◽  
Internal Variables ◽  
Recursive Least Square ◽  
Unknown Parameters ◽  
Actual System ◽  
Highly Nonlinear ◽  
Space Modeling ◽  
Nonlinear State

The paper deals with nonlinear modeling and identification of an electrohydraulic control system for improving its tracking performance. We build the nonlinear state space model for analyzing the highly nonlinear system and then develop a Hammerstein-Wiener (H-W) model which consists of a static input nonlinear block with two-segment polynomial nonlinearities, a linear time-invariant dynamic block, and a static output nonlinear block with single polynomial nonlinearity to describe it. We simplify the H-W model into a linear-in-parameters structure by using the key term separation principle and then use a modified recursive least square method with iterative estimation of internal variables to identify all the unknown parameters simultaneously. It is found that the proposed H-W model approximates the actual system better than the independent Hammerstein, Wiener, and ARX models. The prediction error of the H-W model is about 13%, 54%, and 58% less than the Hammerstein, Wiener, and ARX models, respectively.

GPS-DERIVED SECULAR VELOCITY FIELD AROUND SANGIHE ISLAND AND ITS IMPLICATION TO THE MOLUCCA SEA SEISMICITY

GEOMATIKA ◽  
2020 ◽  
Vol 26 (2) ◽  
pp. 107
Author(s):  
Leni Sophia Heliani ◽  
Cecep Pratama ◽  
Parseno Parseno ◽  
Nurrohmat Widjajanti ◽  
Dwi Lestari
Keyword(s):  
Surface Displacement ◽  
Active Regions ◽  
Least Square ◽  
The Other ◽  
Gps Data ◽  
West Side ◽  
Active Deformation ◽  
Secular Motion ◽  
Small Change ◽  
Linear Least Square

<p><em>Sangihe-Moluccas region is the most active seismicity in Indonesia. Between 2015 to 2018 there is four M6 class earthquake occurred close to the Sangihe-Moluccas region. These seismic active regions representing active deformation which is recorded on installed GPS for both campaign and continuous station. However, the origin of those frequent earthquakes has not been well understood especially related to GPS-derived secular motion. Therefore, we intend to estimate the secular motion inside and around Sangihe island. On the other hand, we also evaluate the effect of seismicity on GPS sites. Since our GPS data were conducted on yearly basis, we used an empirical global model of surface displacement due to coseismic activity. We calculate the offset that may be contained in the GPS site during its period</em><em>. </em><em>We remove the offset and estimate again the secular motion using linear least square. Hence, in comparison with the secular motion without considering the seismicity, we observe small change but systematically shifting the motion. We concluded the seismicity in the Molucca sea from 2015 to 2018 systematically change the secular motion around Sangihe Island at the sub-mm level. Finally, we obtained the secular motion toward each other between the east and west side within 1 to 5.5 cm/year displacement. </em></p>

scholarly journals An Indoor Visible Light Positioning System Using Tilted LEDs with High Accuracy

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 920
Author(s):  
Neha Chaudhary ◽  
Othman Isam Younus ◽  
Luis Nero Alves ◽  
Zabih Ghassemlooy ◽  
Stanislav Zvanovec ◽  
...  
Keyword(s):  
Visible Light ◽  
Polynomial Regression ◽  
Power Level ◽  
Least Square ◽  
Line Of Sight ◽  
Received Power ◽  
Strength Based ◽  
Complex Linear ◽  
Linear Least Square ◽  
First Time

The accuracy of the received signal strength-based visible light positioning (VLP) system in indoor applications is constrained by the tilt angles of transmitters (Txs) and receivers as well as multipath reflections. In this paper, for the first time, we show that tilting the Tx can be beneficial in VLP systems considering both line of sight (LoS) and non-line of sight transmission paths. With the Txs oriented towards the center of the receiving plane (i.e., the pointing center F), the received power level is maximized due to the LoS components on F. We also show that the proposed scheme offers a significant accuracy improvement of up to ~66% compared with a typical non-tilted Tx VLP at a dedicated location within a room using a low complex linear least square algorithm with polynomial regression. The effect of tilting the Tx on the lighting uniformity is also investigated and results proved that the uniformity achieved complies with the European Standard EN 12464-1. Furthermore, we show that the accuracy of VLP can be further enhanced with a minimum positioning error of 8 mm by changing the height of F.

A Modified Algorithm for the Least Squares Identification

1983 ◽  
Vol 105 (1) ◽  
pp. 50-52
Author(s):  
C. Batur
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Mechanical Systems ◽  
Model Structure ◽  
Input Output ◽  
Unknown Parameters ◽  
Estimation Errors ◽  
Usual Practice ◽  
Unknown Disturbances ◽  
Modified Algorithm

To identify the dynamics of mechanical systems, the usual practice is to assume a certain model structure and try to estimate the unknown parameters of this model on the basis of input output observations. For mechanical systems operating under noisy industrial conditions, the number of unknowns of the problem exceeds the number of equations available. It is then inevitable that certain assumptions must be made on the unknown disturbances. This paper assumes that the only reliable feature of the disturbance is its independence of input. This yields a set of assumptions in excess of the minimal requirements and an endeavor has been made to exploit this excess to minimize the parameter estimation errors. Th resulting algorithm is similar to that of the Two Stage Least Squares method [1].

Least Square Regression with lp-Coefficient Regularization

2010 ◽  
Vol 22 (12) ◽  
pp. 3221-3235 ◽  
Author(s):  
Hongzhi Tong ◽  
Di-Rong Chen ◽  
Fenghong Yang
Keyword(s):  
Error Analysis ◽  
Learning Algorithm ◽  
Learning Rate ◽  
Least Square ◽  
Explicit Learning ◽  
Regularization Term ◽  
Least Square Regression ◽  
Primary Focus ◽  
Selection Of

The selection of the penalty functional is critical for the performance of a regularized learning algorithm, and thus it deserves special attention. In this article, we present a least square regression algorithm based on lp-coefficient regularization. Comparing with the classical regularized least square regression, the new algorithm is different in the regularization term. Our primary focus is on the error analysis of the algorithm. An explicit learning rate is derived under some ordinary assumptions.

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