|Commenced in January 1999 || Frequency: Monthly || Edition: International|| Paper Count: 7 |
Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering
Industrial Compressor Anti-Surge Computer Control
The paper presents a compressor anti-surge control
system, that results in maximizing compressor throughput with
pressure standard deviation reduction, increased safety margin
between design point and surge limit line and avoiding possible
machine surge. Alternative control strategies are presented.
UD Covariance Factorization for Unscented Kalman Filter using Sequential Measurements Update
Extended Kalman Filter (EKF) is probably the most
widely used estimation algorithm for nonlinear systems. However,
not only it has difficulties arising from linearization but also many
times it becomes numerically unstable because of computer round off
errors that occur in the process of its implementation. To overcome
linearization limitations, the unscented transformation (UT) was
developed as a method to propagate mean and covariance
information through nonlinear transformations. Kalman filter that
uses UT for calculation of the first two statistical moments is called
Unscented Kalman Filter (UKF). Square-root form of UKF (SRUKF)
developed by Rudolph van der Merwe and Eric Wan to
achieve numerical stability and guarantee positive semi-definiteness
of the Kalman filter covariances. This paper develops another
implementation of SR-UKF for sequential update measurement
equation, and also derives a new UD covariance factorization filter
for the implementation of UKF. This filter is equivalent to UKF but
is computationally more efficient.
Accurate Calculation of Free Frequencies of Beams and Rectangular Plates
An accurate procedure to determine free vibrations of
beams and plates is presented.
The natural frequencies are exact solutions of governing vibration
equations witch load to a nonlinear homogeny system.
The bilinear and linear structures considered simulate a bridge.
The dynamic behavior of this one is analyzed by using the theory of
the orthotropic plate simply supported on two sides and free on the
two others. The plate can be excited by a convoy of constant or
harmonic loads. The determination of the dynamic response of the
structures considered requires knowledge of the free frequencies and
the shape modes of vibrations. Our work is in this context. Indeed,
we are interested to develop a self-consistent calculation of the Eigen
The formulation is based on the determination of the solution of
the differential equations of vibrations. The boundary conditions
corresponding to the shape modes permit to lead to a homogeneous
system. Determination of the noncommonplace solutions of this
system led to a nonlinear problem in Eigen frequencies.
We thus, develop a computer code for the determination of the
eigenvalues. It is based on a method of bisection with interpolation
whose precision reaches 10 -12. Moreover, to determine the
corresponding modes, the calculation algorithm that we develop uses
the method of Gauss with a partial optimization of the "pivots"
combined with an inverse power procedure. The Eigen frequencies
of a plate simply supported along two opposite sides while
considering the two other free sides are thus analyzed. The results
could be generalized with the case of a beam by regarding it as a
plate with low width.
We give, in this paper, some examples of treated cases. The
comparison with results presented in the literature is completely
An Engineering Approach to Forecast Volatility of Financial Indices
By systematically applying different engineering
methods, difficult financial problems become approachable. Using a
combination of theory and techniques such as wavelet transform,
time series data mining, Markov chain based discrete stochastic
optimization, and evolutionary algorithms, this work formulated a
strategy to characterize and forecast non-linear time series. It
attempted to extract typical features from the volatility data sets of
S&P100 and S&P500 indices that include abrupt drops, jumps and
other non-linearity. As a result, accuracy of forecasting has reached
an average of over 75% surpassing any other publicly available
results on the forecast of any financial index.
Hydrothermal Behavior of G-S Magnetically Stabilized Beds Consisting of Magnetic and Non-Magnetic Admixtures
The hydrothermal behavior of a bed consisting of
magnetic and shale oil particle admixtures under the effect of a
transverse magnetic field is investigated. The phase diagram, bed
void fraction are studied under wide range of the operating
conditions i.e., gas velocity, magnetic field intensity and fraction of
the magnetic particles. It is found that the range of the stabilized
regime is reduced as the magnetic fraction decreases. In addition, the
bed voidage at the onset of fluidization decreases as the magnetic
fraction decreases. On the other hand, Nusselt number and
consequently the heat transfer coefficient is found to increase as the
magnetic fraction decreases. An empirical equation is investigated to
relate the effect of the gas velocity, magnetic field intensity and
fraction of the magnetic particles on the heat transfer behavior in the
Multistage Condition Monitoring System of Aircraft Gas Turbine Engine
Researches show that probability-statistical methods
application, especially at the early stage of the aviation Gas Turbine
Engine (GTE) technical condition diagnosing, when the flight
information has property of the fuzzy, limitation and uncertainty is
unfounded. Hence the efficiency of application of new technology
Soft Computing at these diagnosing stages with the using of the
Fuzzy Logic and Neural Networks methods is considered. According
to the purpose of this problem training with high accuracy of fuzzy
multiple linear and non-linear models (fuzzy regression equations)
which received on the statistical fuzzy data basis is made.
For GTE technical condition more adequate model making
dynamics of skewness and kurtosis coefficients- changes are
analysed. Researches of skewness and kurtosis coefficients values-
changes show that, distributions of GTE work parameters have fuzzy
character. Hence consideration of fuzzy skewness and kurtosis
coefficients is expedient.
Investigation of the basic characteristics changes- dynamics of
GTE work parameters allows drawing conclusion on necessity of the
Fuzzy Statistical Analysis at preliminary identification of the
engines' technical condition.
Researches of correlation coefficients values- changes shows
also on their fuzzy character. Therefore for models choice the
application of the Fuzzy Correlation Analysis results is offered.
At the information sufficiency is offered to use recurrent
algorithm of aviation GTE technical condition identification (Hard
Computing technology is used) on measurements of input and output
parameters of the multiple linear and non-linear generalised models
at presence of noise measured (the new recursive Least Squares
The developed GTE condition monitoring system provides stageby-
stage estimation of engine technical conditions.
As application of the given technique the estimation of the new
operating aviation engine technical condition was made.
Navigation of Multiple Mobile Robots using Rule-based-Neuro-Fuzzy Technique
This paper deals with motion planning of multiple
mobile robots. Mobile robots working together to achieve several
objectives have many advantages over single robot system. However,
the planning and coordination between the mobile robots is
extremely difficult. In the present investigation rule-based and rulebased-
neuro-fuzzy techniques are analyzed for multiple mobile
robots navigation in an unknown or partially known environment.
The final aims of the robots are to reach some pre-defined goals.
Based upon a reference motion, direction; distances between the
robots and obstacles; and distances between the robots and targets;
different types of rules are taken heuristically and refined later to find
the steering angle. The control system combines a repelling influence
related to the distance between robots and nearby obstacles and with
an attracting influence between the robots and targets. Then a hybrid
rule-based-neuro-fuzzy technique is analysed to find the steering
angle of the robots. Simulation results show that the proposed rulebased-
neuro-fuzzy technique can improve navigation performance in
complex and unknown environments compared to this simple rulebased