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Weighting Matrices (weighting + matrix)

Distribution by Scientific Domains

Engineering	83%

Selected Abstracts

A neural network approach for structural identification and diagnosis of a building from seismic response data

EARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS, Issue 2 2003
C. S. Huang
Abstract This work presents a novel procedure for identifying the dynamic characteristics of a building and diagnosing whether the building has been damaged by earthquakes, using a back-propagation neural network approach. The dynamic characteristics are directly evaluated from the weighting matrices of the neural network trained by observed acceleration responses and input base excitations. Whether the building is damaged under a large earthquake is assessed by comparing the modal parameters and responses for this large earthquake with those for a small earthquake that has not caused this building any damage. The feasibility of the approach is demonstrated through processing the dynamic responses of a five-storey steel frame, subjected to different strengths of the Kobe earthquake, in shaking table tests. Copyright © 2002 John Wiley & Sons, Ltd. [source]

A further result of the nonlinear mixed H2/H, tracking control problem for robotic systems

JOURNAL OF FIELD ROBOTICS (FORMERLY JOURNAL OF ROBOTIC SYSTEMS), Issue 1 2002
C. Q. Huang
The design objective of a mixed H2/H, control is to find the H2 optimal tracking control law under a prescribed disturbance attenuation level. With the help of the technique of completing the squares, a further result of the mixed H2/H, optimal tracking control problem is presented, by combining it with standard LQ optimal control technique. In this paper, only a nonlinear time-varying Riccati equation is required to solve the problem in the design procedure,instead of two coupled nonlinear time-varying Riccati equations, or two coupled linear algebraic Riccati-Iike equations,with some assumptions made regarding the weighting matrices in the existing results. A closed-form controller for the mixed H2/H, robotic tracking problem is simply constructed with a matrix inequality check. Moreover, it shows that the existing results are the special cases of these results. Finally, detailed comparison is performed by numerical simulation of a two-link robotic manipulator. © 2002 John Wiley & Sons, Inc. [source]

On the synthesis of time-varying LQG weights and noises along optimal control and state trajectories

OPTIMAL CONTROL APPLICATIONS AND METHODS, Issue 3 2006
L. G. Van Willigenburg
Abstract A general approach to control non-linear uncertain systems is to apply a pre-computed nominal optimal control, and use a pre-computed LQG compensator to generate control corrections from the on-line measured data. If the non-linear model, on which the optimal control and LQG compensator design is based, is of sufficient quality, and when the LQG compensator is designed appropriately, the closed-loop control system is approximately optimal. This paper contributes to the selection and computation of the time-varying LQG weighting and noise matrices, which determine the LQG compensator design. It is argued that the noise matrices may be taken time-invariant and diagonal. Three very important considerations concerning the selection of the time-varying LQG weighting matrices are turned into a concrete computational scheme. Thereby, the selection of the time-varying LQG weighting matrices is reduced to selecting three scalar design parameters, each one weighting one consideration. Although the three considerations seem straightforward they may oppose one another. Furthermore, they usually result in time-varying weighting matrices that are indefinite, rather than positive (semi) definite as required for the LQG design. The computational scheme presented in this paper addresses and resolves both problems. By two numerical examples the benefits of our optimal closed-loop control system design are demonstrated and evaluated using Monte Carlo simulation. Copyright © 2005 John Wiley & Sons, Ltd. [source]

Observability of Depth Estimation for a Hand-Eye Robot System

ASIAN JOURNAL OF CONTROL, Issue 3 2002
Chang-Jia Fang
ABSTRACT This paper deals with the depth observability problem of a hand-eye robot system. In contrast to earlier works, this paper presents a complete study of this observability problem. The velocity of the active camera in the hand-eye robot system is considered as the input. The observability of depth estimation is then related to the velocity of the camera. A necessary and sufficient condition for the types of camera velocities necessary to ensure observability is found. This compensates for the results of earlier works, in which the velocity of camera was estimated. The theory is also verified by both simulations and experiments in this paper. Furthermore, a modified LQ visual servo control law is proposed to vary the weighting matrices so that depth estimation is improved while the level of control performance is still retained. [source]

Modelling of small-angle X-ray scattering data using Hermite polynomials

JOURNAL OF APPLIED CRYSTALLOGRAPHY, Issue 4 2001
A. K. Swain
A new algorithm, called the term-selection algorithm (TSA), is derived to treat small-angle X-ray scattering (SAXS) data by fitting models to the scattering intensity using weighted Hermite polynomials. This algorithm exploits the orthogonal property of the Hermite polynomials and introduces an error-reduction ratio test to select the correct model terms or to determine which polynomials are to be included in the model and to estimate the associated unknown coefficients. With no a priori information about particle sizes, it is possible to evaluate the real-space distribution function as well as three- and one-dimensional correlation functions directly from the models fitted to raw experimental data. The success of this algorithm depends on the choice of a scale factor and the accuracy of orthogonality of the Hermite polynomials over a finite range of SAXS data. An algorithm to select a weighted orthogonal term is therefore derived to overcome the disadvantages of the TSA. This algorithm combines the properties and advantages of both weighted and orthogonal least-squares algorithms and is numerically more robust for the estimation of the parameters of the Hermite polynomial models. The weighting feature of the algorithm provides an additional degree of freedom to control the effects of noise and the orthogonal feature enables the reorthogonalization of the Hermite polynomials with respect to the weighting matrix. This considerably reduces the error in orthogonality of the Hermite polynomials. The performance of the algorithm has been demonstrated considering both simulated data and experimental data from SAXS measurements of dewaxed cotton fibre at different temperatures. [source]