Abstract: In this study, a robust intelligent backstepping tracking control (RIBTC) system combined with adaptive output recurrent cerebellar model articulation control (AORCMAC) and H∞ control technique is proposed for wheeled inverted pendulums (WIPs) real-time control with exact system dynamics unknown. Moreover, a robust H∞ controller is designed to attenuate the effect of the residual approximation errors and external disturbances with desired attenuation level. The experimental results indicate that the WIPs can stand upright stably when using the proposed RIBTC.
Abstract: A new class of percolation model in complex networks,
in which nodes are characterized by hidden variables reflecting the
properties of nodes and the occupied probability of each link is
determined by the hidden variables of the end nodes, is studied
in this paper. By the mean field theory, the analytical expressions
for the phase of percolation transition is deduced. It is determined
by the distribution of the hidden variables for the nodes and the
occupied probability between pairs of them. Moreover, the analytical
expressions obtained are checked by means of numerical simulations
on a particular model. Besides, the general model can be applied
to describe and control practical diffusion models, such as disease
diffusion model, scientists cooperation networks, and so on.
Abstract: We developed a method based on quasi-molecular
modelling to simulate the fall of water drops on horizontally smooth
and rough surfaces. Each quasi-molecule was a group of particles
that interacted in a fashion entirely analogous to classical Newtonian
molecular interactions. When a falling water droplet was simulated at
low impact velocity on both smooth and rough surfaces, the droplets
moved periodically (i.e. the droplets moved up and down for a
certain period, finally they stopped moving and reached a steady
state), spreading and recoiling without splash or break-up. Spreading
rates of falling water droplets increased rapidly as time increased
until the spreading rate reached its steady state at time t ~ 0.25 s for
rough surface and t ~ 0.40 s for smooth surface. The droplet height
above both surfaces decreased as time increased, remained constant
after the droplet diameter attained a maximum value and reached its
steady state at time t ~ 0.4 s. However, rough surface had higher
spreading rates of falling water droplets and lower height on the
surface than smooth one.
Abstract: PPG is a potential tool in clinical applications. Among such, the relationship between respiration and PPG signal has attracted attention in past decades. In this research, a bivariate AR spectral estimation method was utilized for the coherence analysis between these two signals. Ten healthy subjects participated in this research with signals measured at different respiratory rates. The results demonstrate that high coherence exists between respiration and PPG signal, whereas the coherence disappears in breath-holding experiments. These results imply that PPG signal reveals the respiratory information. The utilized method may provide an attractive alternative approach for the related researches.
Abstract: In this paper, we focus on the use of knowledge bases
in two different application areas – control of systems with unknown
or strongly nonlinear models (i.e. hardly controllable by the classical
methods), and robot motion planning in eight directions. The first
one deals with fuzzy logic and the paper presents approaches for
setting and aggregating the rules of a knowledge base. Te second one
is concentrated on a case-based reasoning strategy for finding the
path in a planar scene with obstacles.
Abstract: Daily production of information and importance of the sequence of produced data in forecasting future performance of market causes analysis of data behavior to become a problem of analyzing time series. But time series that are very complicated, usually are random and as a result their changes considered being unpredictable. While these series might be products of a deterministic dynamical and nonlinear process (chaotic) and as a result be predictable. Point of Chaotic theory view, complicated systems have only chaotically face and as a result they seem to be unregulated and random, but it is possible that they abide by a specified math formula. In this article, with regard to test of strange attractor and biggest Lyapunov exponent probability of chaos on several foreign exchange rates vs. IRR (Iranian Rial) has been investigated. Results show that data in this market have complex chaotic behavior with big degree of freedom.
Abstract: Determination of nano particle size is substantial since
the nano particle size exerts a significant effect on various properties
of nano materials. Accordingly, proposing non-destructive, accurate
and rapid techniques for this aim is of high interest. There are some
conventional techniques to investigate the morphology and grain size
of nano particles such as scanning electron microscopy (SEM),
atomic force microscopy (AFM) and X-ray diffractometry (XRD).
Vibrational spectroscopy is utilized to characterize different
compounds and applied for evaluation of the average particle size
based on relationship between particle size and near infrared spectra
[1,4] , but it has never been applied in quantitative morphological
analysis of nano materials. So far, the potential application of nearinfrared
(NIR) spectroscopy with its ability in rapid analysis of
powdered materials with minimal sample preparation, has been
suggested for particle size determination of powdered
pharmaceuticals. The relationship between particle size and diffuse
reflectance (DR) spectra in near infrared region has been applied to
introduce a method for estimation of particle size. Back propagation
artificial neural network (BP-ANN) as a nonlinear model was applied
to estimate average particle size based on near infrared diffuse
reflectance spectra. Thirty five different nano TiO2 samples with
different particle size were analyzed by DR-FTNIR spectrometry and
the obtained data were processed by BP- ANN.
Abstract: This study was conducted to explore the effects of two
countries model comparison program in Taiwan and Singapore in
TIMSS database. The researchers used Multi-Group Hierarchical
Linear Modeling techniques to compare the effects of two different
country models and we tested our hypotheses on 4,046 Taiwan
students and 4,599 Singapore students in 2007 at two levels: the class
level and student (individual) level. Design quality is a class level
variable. Student level variables are achievement and self-confidence.
The results challenge the widely held view that retention has a positive
impact on self-confidence. Suggestions for future research are
discussed.
Abstract: The crop rice is the staple food of most Sierra Leone
with no close substitute. However, its cultivation has been on its last
legs over the years. The decline in the domestic rice cultivation has
had vicious socio-economic implications such as hiking consumer
prices, balance of payment dilemmas with debt burden. The objective
of this study is thus, to assess the effect of the shift of rural labour
towards non-agricultural sectors on rice cultivation. The tools utilized
for analyzing the problem under consideration involved a thorough
descriptive statistics and generalized linear model using OLS
technique. Increased rural population was established positive and
significant in affecting rice cultivation. Fertilizer utilization was
insignificant in rice cultivation. For reducing the shift of rural labor
force towards nonagricultural sectors, the government should make
the agricultural sector very lucrative.
Abstract: In this paper, the full state feedback controllers
capable of regulating and tracking the speed trajectory are presented.
A fourth order nonlinear mean value model of a 448 kW turbocharged
diesel engine published earlier is used for the purpose.
For designing controllers, the nonlinear model is linearized and
represented in state-space form. Full state feedback controllers
capable of meeting varying speed demands of drivers are presented.
Main focus here is to investigate sensitivity of the controller to the
perturbations in the parameters of the original nonlinear model.
Suggested controller is shown to be highly insensitive to the
parameter variations. This indicates that the controller is likely
perform with same accuracy even after significant wear and tear of
engine due to its use for years.
Abstract: This paper deals with the conceptual design of the
new aeroelastic demonstrator for the whirl flutter simulation. The
paper gives a theoretical background of the whirl flutter phenomenon
and describes the events of the whirl flutter occurrence in the
aerospace practice. The second part is focused on the experimental
research of the whirl flutter on aeroelastic similar models. Finally the
concept of the new aeroelastic demonstrator is described. The
demonstrator represents the wing and engine of the twin turboprop
commuter aircraft including a driven propeller. It allows the changes
of the main structural parameters influencing the whirl flutter
stability characteristics. It is intended for the experimental
investigation of the whirl flutter in the wind tunnel. The results will
be utilized for validation of analytical methods and software tools.
Abstract: Based on the feature of model disturbances and uncertainty being compensated dynamically in auto – disturbances-rejection-controller (ADRC), a new method using ADRC is proposed for the decoupling control of dispenser longitudinal movement in big flight envelope. Developed from nonlinear model directly, ADRC is especially suitable for dynamic model that has big disturbances. Furthermore, without changing the structure and parameters of the controller in big flight envelope, this scheme can simplify the design of flight control system. The simulation results in big flight envelope show that the system achieves high dynamic performance, steady state performance and the controller has strong robustness.
Abstract: Maintenance is one of the most important activities in
the shipyard industry. However, sometimes it is not supported by
adequate services from the shipyard, where inaccuracy in estimating
the duration of the ship maintenance is still common. This makes
estimation of ship maintenance duration is crucial. This study uses
Data Mining approach, i.e., CART (Classification and Regression
Tree) to estimate the duration of ship maintenance that is limited to
dock works or which is known as dry docking. By using the volume
of dock works as an input to estimate the maintenance duration, 4
classes of dry docking duration were obtained with different linear
model and job criteria for each class. These linear models can then be
used to estimate the duration of dry docking based on job criteria.
Abstract: Enhancement of the performance of a reverse osmosis
(RO) unit through periodic control is studied. The periodic control
manipulates the feed pressure and flow rate of the RO unit. To ensure
the periodic behavior of the inputs, the manipulated variables (MV)
are transformed into the form of sinusoidal functions. In this case, the
amplitude and period of the sinusoidal functions become the
surrogate MV and are thus regulated via nonlinear model predictive
control algorithm. The simulation results indicated that the control
system can generate cyclic inputs necessary to enhance the closedloop
performance in the sense of increasing the permeate production
and lowering the salt concentration. The proposed control system can
attain its objective with arbitrary set point for the controlled outputs.
Successful results were also obtained in the presence of modeling
errors.
Abstract: 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 workand output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-by-stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.
Abstract: In this paper, a nonlinear model predictive swing-up
and stabilizing sliding controller is proposed for an inverted
pendulum-cart system. In the swing up phase, the nonlinear model
predictive control is formulated as a nonlinear programming problem
with energy based objective function. By solving this problem at
each sampling instant, a sequence of control inputs that optimize the
nonlinear objective function subject to various constraints over a
finite horizon are obtained. Then, this control drives the pendulum to
a predefined neighborhood of the upper equilibrium point, at where
sliding mode based model predictive control is used to stabilize the
systems with the specified constraints. It is shown by the simulations
that, due to the way of formulating the problem, short horizon
lengths are sufficient for attaining the swing up goal.