scholarly journals Data compression for estimation of the physical parameters of stable and unstable linear systems

Automatica ◽  
2005 ◽  
Vol 41 (8) ◽  
pp. 1313-1321 ◽  
Author(s):  
Peter J. Gawthrop ◽  
Liuping Wang
1981 ◽  
Vol 21 (06) ◽  
pp. 699-708
Author(s):  
Paul E. Saylor

Abstract Reservoir simulation yields a system of linear algebraic equations, Ap=q, that may be solved by Richardson's iterative method, p(k+1)=p(k)+tkr(k), where r(k)=q-Ap(k) is the residual and t0, . . . tk are acceleration parameters. The incomplete factorization, Ka, of the strongly implicit procedure (SIP) yields an improvement of Richardson's method, p(k+1)=p(k)+tkKa−1r(k). Parameter a originates from SIP. The product of the L and U factors produced by SIP gives Ka=LU. The best values of the tk acceleration parameters may be computed dynamically by an efficient algorithm; the best value of a must be found by trial and error, which is not hard for only one value. The advantages of the method are (1) it always converges, (2) with the exception of the a parameter, parameters are computed dynamically, and (3) convergence is efficient for test problems characterized by heterogeneities and transmissibilities varying over 10 orders of magnitude. The test problems originate from field data and were suggested by industry personnel as particularly difficult. Dynamic computation of parameters is also a feature of the conjugate gradient method, but the iteration described here does not require A to be symmetric. Matrix Ka−1 A must be such that the real part of each eigenvalue is nonnegative, or the real part of each is nonpositive, but not both positive and negative. It is in this sense that the method always converges. This condition is satisfied by many simulator-generated matrices. The method also may be applied to matrices arising from the simulation of other processes, such as chemical flooding. Introduction The solution of a linear algebraic system, Ap=q, is a basic, costly step in the numerical simulation of a hydrocarbon reservoir. Many current solution methods are impractical for large linear systems arising from three-dimensional simulations or from reservoirs characterized by widely varying and discontinuous physical parameters. An iterative solution is described with these two main advantages:it is efficient for difficult problems andthe selection of iteration parameters is straightforward. The method is Richardson's method applied to a preconditioned linear system. Matrix A may be symmetric or nonsymmetric. In the simulation of multiphase flow, it is usually nonsymmetric. Convergence behavior is shown for four examples. Two of these, Examples 3 and 4, were provided by an industry laboratory (Exxon Production Research Co.), and were suggested by personnel as especially difficult to solve; SIP failed to converge and only the diagonal method1 was effective. Convergence of Richardson's method is compared with the diagonal method using data from a laboratory run. The other two examples are: Example 1, a matrix not difficult to solve, generated from field data, and Example 2, a variant of a difficult matrix described by Stone.2 The easy matrix of Example 1 is included to show the performance of Richardson's method (with preconditioning) on a simple problem.


1995 ◽  
Vol 30 (6) ◽  
pp. 841-860 ◽  
Author(s):  
Julius S. Bendat ◽  
Robert N. Coppolino ◽  
Paul A. Palo

2004 ◽  
Vol 71 (1) ◽  
pp. 131-134 ◽  
Author(s):  
R. M. Bulatovic

Free motions of viscously damped linear systems are studied. A heavily damped multi-degree-of-freedom system is defined as one for which all its eigenvalues are real, negative, and semi-simple. Several results are obtained which state conditions for the heavy damping of the system. The conditions are given directly in terms of the coefficients of system matrices and these conditions may yield design constraints in terms of the physical parameters of the system. An example illustrates the validity and usefulness of the presented results.


Author(s):  
Mohammad Reza Amini ◽  
Mahdi Shahbakhti ◽  
Selina Pan

The performance of a conventional model-based controller significantly depends on the accuracy of the modeled dynamics. The model of a plant’s dynamics is subjected to errors in estimating the numerical values of the physical parameters, and variations over operating environment conditions and time. These errors and variations in the parameters of a model are the major sources of uncertainty within the controller structure. Digital implementation of controller software on an actual electronic control unit (ECU) introduces another layer of uncertainty at the controller inputs/outputs. The implementation uncertainties are mostly due to data sampling and quantization via the analog-to-digital conversion (ADC) unit. The failure to address the model and ADC uncertainties during the early stages of a controller design cycle results in a costly and time consuming verification and validation (V&V) process. In this paper, new formulations of the first and second order discrete sliding mode controllers (DSMC) are presented for a general class of uncertain linear systems. The knowledge of the ADC imprecisions is incorporated into the proposed DSMCs via an online ADC uncertainty prediction mechanism to improve the controller robustness characteristics. Moreover, the DSMCs are equipped with adaptation laws to remove two different types of modeling uncertainties (multiplicative and additive) from the parameters of the linear system model. The proposed adaptive DSMCs are evaluated on a DC motor speed control problem in real-time using a processor-in-the-loop (PIL) setup with an actual ECU. The results show that the proposed SISO and MIMO second order DSMCs improve the conventional SISO first order DSMC tracking performance by 69% and 84%, respectively. Moreover, the proposed adaptation mechanism is able to remove the uncertainties in the model by up to 90%.


1965 ◽  
Vol 5 ◽  
pp. 120-130
Author(s):  
T. S. Galkina

It is necessary to have quantitative estimates of the intensity of lines (both absorption and emission) to obtain the physical parameters of the atmosphere of components.Some years ago at the Crimean observatory we began the spectroscopic investigation of close binary systems of the early spectral type with components WR, Of, O, B to try and obtain more quantitative information from the study of the spectra of the components.


Author(s):  
J.T. Fourie

Contamination in electron microscopes can be a serious problem in STEM or in situations where a number of high resolution micrographs are required of the same area in TEM. In modern instruments the environment around the specimen can be made free of the hydrocarbon molecules, which are responsible for contamination, by means of either ultra-high vacuum or cryo-pumping techniques. However, these techniques are not effective against hydrocarbon molecules adsorbed on the specimen surface before or during its introduction into the microscope. The present paper is concerned with a theory of how certain physical parameters can influence the surface diffusion of these adsorbed molecules into the electron beam where they are deposited in the form of long chain carbon compounds by interaction with the primary electrons.


Author(s):  
Linda Sicko-Goad

Although the use of electron microscopy and its varied methodologies is not usually associated with ecological studies, the types of species specific information that can be generated by these techniques are often quite useful in predicting long-term ecosystem effects. The utility of these techniques is especially apparent when one considers both the size range of particles found in the aquatic environment and the complexity of the phytoplankton assemblages.The size range and character of organisms found in the aquatic environment are dependent upon a variety of physical parameters that include sampling depth, location, and time of year. In the winter months, all the Laurentian Great Lakes are uniformly mixed and homothermous in the range of 1.1 to 1.7°C. During this time phytoplankton productivity is quite low.


Author(s):  
P.-F. Staub ◽  
C. Bonnelle ◽  
F. Vergand ◽  
P. Jonnard

Characterizing dimensionally and chemically nanometric structures such as surface segregation or interface phases can be performed efficiently using electron probe (EP) techniques at very low excitation conditions, i.e. using small incident energies (0.5<E0<5 keV) and low incident overvoltages (1<U0<1.7). In such extreme conditions, classical analytical EP models are generally pushed to their validity limits in terms of accuracy and physical consistency, and Monte-Carlo simulations are not convenient solutions as routine tools, because of their cost in computing time. In this context, we have developed an intermediate procedure, called IntriX, in which the ionization depth distributions Φ(ρz) are numerically reconstructed by integration of basic macroscopic physical parameters describing the electron beam/matter interaction, all of them being available under pre-established analytical forms. IntriX’s procedure consists in dividing the ionization depth distribution into three separate contributions:


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