Abstract: We present a new subband adaptive filter (R-SAF)
which is robust against impulsive noise in system identification. To
address the vulnerability of adaptive filters based on the L2-norm
optimization criterion against impulsive noise, the R-SAF comes from
the L1-norm optimization criterion with a constraint on the energy
of the weight update. Minimizing L1-norm of the a posteriori error
in each subband with a constraint on minimum disturbance gives
rise to the robustness against the impulsive noise and the capable
convergence performance. Experimental results clearly demonstrate
that the proposed R-SAF outperforms the classical adaptive filtering
algorithms when impulsive noise as well as background noise exist.
Abstract: In this work, we use the Fault detection and isolation and the Fault tolerant control based on sliding mode observer in order to introduce the well diagnosis of a nonlinear system. The robustness of the proposed observer for the two techniques is tested through a physical example. The results in this paper show the interaction between the Fault tolerant control and the Diagnosis procedure.
Abstract: This paper outlines the development of an
experimental technique in quantifying supersonic jet flows, in an
attempt to avoid seeding particle problems frequently associated with
particle-image velocimetry (PIV) techniques at high Mach numbers.
Based on optical flow algorithms, the idea behind the technique
involves using high speed cameras to capture Schlieren images of the
supersonic jet shear layers, before they are subjected to an adapted
optical flow algorithm based on the Horn-Schnuck method to
determine the associated flow fields. The proposed method is capable
of offering full-field unsteady flow information with potentially
higher accuracy and resolution than existing point-measurements or
PIV techniques. Preliminary study via numerical simulations of a
circular de Laval jet nozzle successfully reveals flow and shock
structures typically associated with supersonic jet flows, which serve
as useful data for subsequent validation of the optical flow based
experimental results. For experimental technique, a Z-type Schlieren
setup is proposed with supersonic jet operated in cold mode,
stagnation pressure of 4 bar and exit Mach of 1.5. High-speed singleframe
or double-frame cameras are used to capture successive
Schlieren images. As implementation of optical flow technique to
supersonic flows remains rare, the current focus revolves around
methodology validation through synthetic images. The results of
validation test offers valuable insight into how the optical flow
algorithm can be further improved to improve robustness and
accuracy. Despite these challenges however, this supersonic flow
measurement technique may potentially offer a simpler way to
identify and quantify the fine spatial structures within the shock shear
layer.
Abstract: Orthogonal Frequency Division Multiplexing
(OFDM) has been used in many advanced wireless communication
systems due to its high spectral efficiency and robustness to
frequency selective fading channels. However, the major concern
with OFDM system is the high peak-to-average power ratio (PAPR)
of the transmitted signal. Some of the popular techniques used for
PAPR reduction in OFDM system are conventional partial transmit
sequences (CPTS) and clipping. In this paper, a parallel
combination/hybrid scheme of PAPR reduction using clipping and
CPTS algorithms is proposed. The proposed method intelligently
applies both the algorithms in order to reduce both PAPR as well as
computational complexity. The proposed scheme slightly degrades
bit error rate (BER) performance due to clipping operation and it can
be reduced by selecting an appropriate value of the clipping ratio
(CR). The simulation results show that the proposed algorithm
achieves significant PAPR reduction with much reduced
computational complexity.
Abstract: In this paper, a robust fault detection and isolation
(FDI) scheme is developed to monitor a multivariable nonlinear
chemical process called the Chylla-Haase polymerization reactor,
when it is under the cascade PI control. The scheme employs a radial
basis function neural network (RBFNN) in an independent mode to
model the process dynamics, and using the weighted sum-squared
prediction error as the residual. The Recursive Orthogonal Least
Squares algorithm (ROLS) is employed to train the model to
overcome the training difficulty of the independent mode of the
network. Then, another RBFNN is used as a fault classifier to isolate
faults from different features involved in the residual vector. Several
actuator and sensor faults are simulated in a nonlinear simulation of
the reactor in Simulink. The scheme is used to detect and isolate the
faults on-line. The simulation results show the effectiveness of the
scheme even the process is subjected to disturbances and
uncertainties including significant changes in the monomer feed rate,
fouling factor, impurity factor, ambient temperature, and
measurement noise. The simulation results are presented to illustrate
the effectiveness and robustness of the proposed method.
Abstract: Concurrent planning of project scheduling and
material ordering has been increasingly addressed within last decades
as an approach to improve the project execution costs. Therefore, we
have taken the problem into consideration in this paper, aiming to
maximize schedules quality robustness, in addition to minimize the
relevant costs. In this regard, a bi-objective mathematical model is
developed to formulate the problem. Moreover, it is possible to
utilize the all-unit discount for materials purchasing. The problem is
then solved by the E-constraint method, and the Pareto front is
obtained for a variety of robustness values. The applicability and
efficiency of the proposed model is tested by different numerical
instances, finally.
Abstract: Liver segmentation from medical images poses more
challenges than analogous segmentations of other organs. This
contribution introduces a liver segmentation method from a series of
computer tomography images. Overall, we present a novel method for
segmenting liver by coupling density matching with shape priors.
Density matching signifies a tracking method which operates via
maximizing the Bhattacharyya similarity measure between the
photometric distribution from an estimated image region and a model
photometric distribution. Density matching controls the direction of
the evolution process and slows down the evolving contour in regions
with weak edges. The shape prior improves the robustness of density
matching and discourages the evolving contour from exceeding liver’s
boundaries at regions with weak boundaries. The model is
implemented using a modified distance regularized level set (DRLS)
model. The experimental results show that the method achieves a
satisfactory result. By comparing with the original DRLS model, it is
evident that the proposed model herein is more effective in addressing
the over segmentation problem. Finally, we gauge our performance of
our model against matrices comprising of accuracy, sensitivity, and
specificity.
Abstract: This paper presents the advantages of fuzzy control use in technological processes control. The paper presents a real application of the Linguistic Fuzzy-Logic Control, developed at the University of Ostrava for the control of physical models in the Intelligent Systems Laboratory. The paper presents an example of a sensitive non-linear model, such as a magnetic levitation model and obtained results which show how modern information technologies can help to solve actual technical problems. A special method based on the LFLC controller with partial components is presented in this paper followed by the method of automatic context change, which is very helpful to achieve more accurate control results. The main advantage of the used system is its robustness in changing conditions demonstrated by comparing with conventional PID controller. This technology and real models are also used as a background for problem-oriented teaching, realized at the department for master students and their collaborative as well as individual final projects.
Abstract: In recent years, new techniques for solving complex
problems in engineering are proposed. One of these techniques is
JPSO algorithm. With innovative changes in the nature of the jump
algorithm JPSO, it is possible to construct a graph-based solution
with a new algorithm called G-JPSO. In this paper, a new algorithm
to solve the optimal control problem Fletcher-Powell and optimal
control of pumps in water distribution network was evaluated.
Optimal control of pumps comprise of optimum timetable operation
(status on and off) for each of the pumps at the desired time interval.
Maximum number of status on and off for each pumps imposed to the
objective function as another constraint. To determine the optimal
operation of pumps, a model-based optimization-simulation
algorithm was developed based on G-JPSO and JPSO algorithms.
The proposed algorithm results were compared well with the ant
colony algorithm, genetic and JPSO results. This shows the
robustness of proposed algorithm in finding near optimum solutions
with reasonable computational cost.
Abstract: This paper presents a speed estimation scheme based
on second-order sliding-mode Super Twisting Algorithm (STA) and
Model Reference Adaptive System (MRAS) estimation theory for
Sensorless control of multiphase induction machine. A stator current
observer is designed based on the STA, which is utilized to take the
place of the reference voltage model of the standard MRAS
algorithm. The observer is insensitive to the variation of rotor
resistance and magnetizing inductance when the states arrive at the
sliding mode. Derivatives of rotor flux are obtained and designed as
the state of MRAS, thus eliminating the integration. Compared with
the first-order sliding-mode speed estimator, the proposed scheme
makes full use of the auxiliary sliding-mode surface, thus alleviating
the chattering behavior without increasing the complexity. Simulation
results show the robustness and effectiveness of the proposed
scheme.
Abstract: In this paper, a spatial multiple-kernel fuzzy C-means (SMKFCM) algorithm is introduced for segmentation problem. A linear combination of multiples kernels with spatial information is used in the kernel FCM (KFCM) and the updating rules for the linear coefficients of the composite kernels are derived as well. Fuzzy cmeans (FCM) based techniques have been widely used in medical image segmentation problem due to their simplicity and fast convergence. The proposed SMKFCM algorithm provides us a new flexible vehicle to fuse different pixel information in medical image segmentation and detection of MR images. To evaluate the robustness of the proposed segmentation algorithm in noisy environment, we add noise in medical brain tumor MR images and calculated the success rate and segmentation accuracy. From the experimental results it is clear that the proposed algorithm has better performance than those of other FCM based techniques for noisy medical MR images.
Abstract: Electrohydraulic servo system have been used in
industry in a wide number of applications. Its dynamics are highly
nonlinear and also have large extent of model uncertainties and
external disturbances. In this paper, a robust back-stepping control
(RBSC) scheme is proposed to overcome the problem of disturbances
and system uncertainties effectively and to improve the tracking
performance of EHS systems. In order to implement the proposed
control scheme, the system uncertainties in EHS systems are
considered as total leakage coefficient and effective oil volume. In
addition, in order to obtain the virtual controls for stabilizing system,
the update rule for the system uncertainty term is induced by
the Lyapunov control function (LCF). To verify the performance and
robustness of the proposed control system, computer simulation of
the proposed control system using Matlab/Simulink Software
is executed. From the computer simulation, it was found that the
RBSC system produces the desired tracking performance and has
robustness to the disturbances and system uncertainties of EHS
systems.
Abstract: Batch production plants provide a wide range of
scheduling problems. In pharmaceutical industries a batch process
is usually described by a recipe, consisting of an ordering of tasks
to produce the desired product. In this research work we focused
on pharmaceutical production processes requiring the culture of
a microorganism population (i.e. bacteria, yeasts or antibiotics).
Several sources of uncertainty may influence the yield of the culture
processes, including (i) low performance and quality of the cultured
microorganism population or (ii) microbial contamination. For
these reasons, robustness is a valuable property for the considered
application context. In particular, a robust schedule will not collapse
immediately when a cell of microorganisms has to be thrown away
due to a microbial contamination. Indeed, a robust schedule should
change locally in small proportions and the overall performance
measure (i.e. makespan, lateness) should change a little if at all.
In this research work we formulated a constraint programming
optimization (COP) model for the robust planning of antibiotics
production. We developed a discrete-time model with a multi-criteria
objective, ordering the different criteria and performing a
lexicographic optimization. A feasible solution of the proposed
COP model is a schedule of a given set of tasks onto available
resources. The schedule has to satisfy tasks precedence constraints,
resource capacity constraints and time constraints. In particular
time constraints model tasks duedates and resource availability
time windows constraints. To improve the schedule robustness, we
modeled the concept of (a, b) super-solutions, where (a, b) are input
parameters of the COP model. An (a, b) super-solution is one in
which if a variables (i.e. the completion times of a culture tasks)
lose their values (i.e. cultures are contaminated), the solution can be
repaired by assigning these variables values with a new values (i.e.
the completion times of a backup culture tasks) and at most b other
variables (i.e. delaying the completion of at most b other tasks).
The efficiency and applicability of the proposed model is
demonstrated by solving instances taken from a real-life
pharmaceutical company. Computational results showed that
the determined super-solutions are near-optimal.
Abstract: This paper presents a power control for a Doubly Fed
Induction Generator (DFIG) using in Wind Energy Conversion
System (WECS) connected to the grid. The proposed control strategy
employs two nonlinear controllers, Backstipping (BSC) and slidingmode
controller (SMC) scheme to directly calculate the required
rotor control voltage so as to eliminate the instantaneous errors of
active and reactive powers. In this paper the advantages of BSC and
SMC are presented, the performance and robustness of this two
controller’s strategy are compared between them. First, we present a
model of wind turbine and DFIG machine, then a synthesis of the
controllers and their application in the DFIG power control.
Simulation results on a 1.5MW grid-connected DFIG system are
provided by MATLAB/Simulink.
Abstract: A novel chromium-free protective coating films based
on a zeolite coating was growing onto a FeCrAlloy metal using in –
situ hydrothermal method. The zeolite film was obtained using in-situ
crystallization process that is capable of coating large surfaces with
complex shape and in confined spaces has been developed. The
zeolite coating offers an advantage of a high mechanical stability and
thermal stability. The physicochemical properties were investigated
using X-ray diffraction (XRD), Electron Microscopy (SEM), Energy
Dispersive X–ray Analysis (EDX) and Thermogravimetric Analysis
(TGA). The transition from oxide-on-alloy wires to hydrothermally
synthesised uniformly zeolite coated surfaces was followed using
SEM and XRD. In addition, the robustness of the prepared coating
was confirmed by subjecting these to thermal cycling (ambient to
550oC).
Abstract: We used live E. coli containing synthetic genetic
oscillators to study how the degree of synchrony between the genetic
circuits of sister cells changes with temperature. We found that both
the mean and the variability of the degree of synchrony between the
fluorescence signals from sister cells are affected by temperature.
Also, while most pairs of sister cells were found to be highly
synchronous in each condition, the number of asynchronous pairs
increased with increasing temperature, which was found to be due to
disruptions in the oscillations. Finally we provide evidence that these
disruptions tend to affect multiple generations as opposed to
individual cells. These findings provide insight in how to design
more robust synthetic circuits and in how cell division can affect their
dynamics.
Abstract: In this paper, we proposed a novel SCR (Silicon Controlled
Rectifier) - based ESD (Electrostatic Discharge) protection device for I/O
and power clamp. The proposed device has a higher holding voltage
characteristic than conventional SCR. These characteristics enable to have
latch-up immunity under normal operating conditions as well as superior full
chip ESD protection. The proposed device was analyzed to figure out
electrical characteristics and tolerance robustness in term of individual
design parameters (D1, D2, D3). They are investigated by using the
Synopsys TCAD simulator. As a result of simulation, holding voltage
increased with different design parameters. The holding voltage of the
proposed device changes from 3.3V to 7.9V. Also, N-Stack structure ESD
device with the high holding voltage is proposed. In the simulation results,
2-stack has holding voltage of 6.8V and 3-stack has holding voltage of
10.5V. The simulation results show that holding voltage of stacking
structure can be larger than the operation voltage of high-voltage
application.
Abstract: Experimental economics is subject to criticism with
regards to frequently discussed the trade-off between internal and
external validity requirements, which seems to be critically flawed.
This paper evaluates incompatibility of trade-off condition and
condition of internal validity as a prerequisite for external validity. In
addition, it outlines the imprecise concept of artificiality, which is
found to be rather improving the external validity and seems to
strengthen the illusory status of external versus internal validity
tension. Internal validity is further analyzed with regards to Duhem-
Quine problem, where unpredictability argument is significantly
weakened trough application of inductivism within the illustrative
hypothetical-deductive model. Our discussion partially weakens
critical arguments related to the robustness of results in experimental
economics, if the perfectly controlled experimental environment is
secured.
Abstract: Any signal transmitted over a channel is corrupted by noise and interference. A host of channel coding techniques has been proposed to alleviate the effect of such noise and interference. Among these Turbo codes are recommended, because of increased capacity at higher transmission rates and superior performance over convolutional codes. The multimedia elements which are associated with ample amount of data are best protected by Turbo codes. Turbo decoder employs Maximum A-posteriori Probability (MAP) and Soft Output Viterbi Decoding (SOVA) algorithms. Conventional Turbo coded systems employ Equal Error Protection (EEP) in which the protection of all the data in an information message is uniform. Some applications involve Unequal Error Protection (UEP) in which the level of protection is higher for important information bits than that of other bits. In this work, enhancement to the traditional Log MAP decoding algorithm is being done by using optimized scaling factors for both the decoders. The error correcting performance in presence of UEP in Additive White Gaussian Noise channel (AWGN) and Rayleigh fading are analyzed for the transmission of image with Discrete Cosine Transform (DCT) as source coding technique. This paper compares the performance of log MAP, Modified log MAP (MlogMAP) and Enhanced log MAP (ElogMAP) algorithms used for image transmission. The MlogMAP algorithm is found to be best for lower Eb/N0 values but for higher Eb/N0 ElogMAP performs better with optimized scaling factors. The performance comparison of AWGN with fading channel indicates the robustness of the proposed algorithm. According to the performance of three different message classes, class3 would be more protected than other two classes. From the performance analysis, it is observed that ElogMAP algorithm with UEP is best for transmission of an image compared to Log MAP and MlogMAP decoding algorithms.
Abstract: Electrohydraulic servo system have been used in industry in a wide number of applications. Its dynamics are highly nonlinear and also have large extent of model uncertainties and external disturbances. In this paper, a robust back-stepping control (RBSC) scheme is proposed to overcome the problem of disturbances and system uncertainties effectively and to improve the tracking performance of EHS systems. In order to implement the proposed control scheme, the system uncertainties in EHS systems are considered as total leakage coefficient and effective oil volume. In addition, in order to obtain the virtual controls for stabilizing system, the update rule for the system uncertainty term is induced by the Lyapunov control function (LCF). To verify the performance and robustness of the proposed control system, computer simulation of the proposed control system using Matlab/Simulink Software is executed. From the computer simulation, it was found that the RBSC system produces the desired tracking performance and has robustness to the disturbances and system uncertainties of EHS systems.