Efficient Antenna Array Beamforming with Robustness against Random Steering Mismatch
This paper deals with the problem of using antenna sensors for adaptive beamforming in the presence of random steering mismatch. We present an efficient adaptive array beamformer with robustness to deal with the considered problem. The robustness of the proposed beamformer comes from the efficient designation of the steering vector. Using the received array data vector, we construct an appropriate correlation matrix associated with the received array data vector and a correlation matrix associated with signal sources. Then, the eigenvector associated with the largest eigenvalue of the constructed signal correlation matrix is designated as an appropriate estimate of the steering vector. Finally, the adaptive weight vector required for adaptive beamforming is obtained by using the estimated steering vector and the constructed correlation matrix of the array data vector. Simulation results confirm the effectiveness of the proposed method.
Redundancy Component Matrix and Structural Robustness
We introduce the redundancy matrix that expresses clearly the geometrical/topological configuration of the structure. With the matrix, the redundancy of the structure is resolved into redundant components and assigned to each member or rigid joint. The values of the diagonal elements in the matrix indicates the importance of the corresponding members or rigid joints, and the geometrically correlations can be shown with the non-diagonal elements. If a member or rigid joint failures, reassignment of the redundant components can be calculated with the recursive method given in the paper. By combining the indexes of reliability and redundancy components, we define an index concerning the structural robustness. To further explain the properties of the redundancy matrix, we cited several examples of statically indeterminate structures, including two trusses and a rigid frame. With the examples, some simple results and the properties of the matrix are discussed. The examples also illustrate that the redundancy matrix and the relevant concepts are valuable in structural safety analysis.
H-Infinity and RST Position Controllers of Rotary Traveling Wave Ultrasonic Motor
Traveling Wave Ultrasonic Motor (TWUM) is a compact, precise, and silent actuator generating high torque at low speed without gears. Moreover, the TWUM has a high holding torque without supply, which makes this motor as an attractive solution for holding position of robotic arms. However, their nonlinear dynamics, and the presence of load-dependent dead zones often limit their use. Those issues can be overcome in closed loop with effective and precise controllers. In this paper, robust H-infinity (H∞) and discrete time RST position controllers are presented. The H∞ controller is designed in continuous time with additional weighting filters to ensure the robustness in the case of uncertain motor model and external disturbances. Robust RST controller based on the pole placement method is also designed and compared to the H∞. Simulink model of TWUM is used to validate the stability and the robustness of the two proposed controllers.
Actuator Fault Detection and Fault Tolerant Control of a Nonlinear System Using Sliding Mode Observer
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.
Impulsive Noise-Resilient Subband Adaptive Filter
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.
Variable Regularization Parameter Normalized Least Mean Square Adaptive Filter
We present a normalized LMS (NLMS) algorithm
with robust regularization. Unlike conventional NLMS with the
fixed regularization parameter, the proposed approach dynamically
updates the regularization parameter. By exploiting a gradient
descent direction, we derive a computationally efficient and robust
update scheme for the regularization parameter. In simulation, we
demonstrate the proposed algorithm outperforms conventional NLMS
algorithms in terms of convergence rate and misadjustment error.
Sparsity-Aware and Noise-Robust Subband Adaptive Filter
This paper presents a subband adaptive filter (SAF)
for a system identification where an impulse response is sparse
and disturbed with an impulsive noise. Benefiting from the uses
of l1-norm optimization and l0-norm penalty of the weight vector
in the cost function, the proposed l0-norm sign SAF (l0-SSAF)
achieves both robustness against impulsive noise and much improved
convergence behavior than the classical adaptive filters. Simulation
results in the system identification scenario confirm that the proposed
l0-norm SSAF is not only more robust but also faster and more
accurate than its counterparts in the sparse system identification in
the presence of impulsive noise.
Synchrony between Genetic Repressilators in Sister Cells in Different Temperatures
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
Robust Fault Diagnosis for Wind Turbine Systems Subjected to Multi-Faults
Operations, maintenance and reliability of wind
turbines have received much attention over the years due to the rapid
expansion of wind farms. This paper explores early fault diagnosis
technique for a 5MW wind turbine system subjected to multiple
faults, where genetic optimization algorithm is employed to make the
residual sensitive to the faults, but robust against disturbances. The
proposed technique has a potential to reduce the downtime mostly
caused by the breakdown of components and exploit the productivity
consistency by providing timely fault alarms. Simulation results show
the effectiveness of the robust fault detection methods used under
Characteristic Function in Estimation of Probability Distribution Moments
In this article the problem of distributional moments estimation is considered. The new approach of moments estimation based on usage of the characteristic function is proposed. By statistical simulation technique author shows that new approach has some robust properties. For calculation of the derivatives of characteristic function there is used numerical differentiation. Obtained results confirmed that author’s idea has a certain working efficiency and it can be recommended for any statistical applications.
Capacity of Anchors in Structural Connections
When dealing with safety in structures, the connections between structural components play an important role. Robustness of a structure as a whole depends both on the load- bearing capacity of the structural component and on the structures capacity to resist total failure, even though a local failure occurs in a component or a connection between components. To avoid progressive collapse it is necessary to be able to carry out a design for connections. A connection may be executed with anchors to withstand local failure of the connection in structures built with prefabricated components. For the design of these anchors, a model is developed for connections in structures performed in prefabricated autoclaved aerated concrete components. The design model takes into account the effect of anchors placed close to the edge, which may result in splitting failure. Further the model is developed to consider the effect of reinforcement diameter and anchor depth. The model is analytical and theoretically derived assuming a static equilibrium stress distribution along the anchor. The theory is compared to laboratory test, including the relevant parameters and the model is refined and theoretically argued analyzing the observed test results. The method presented can be used to improve safety in structures or even optimize the design of the connections
State Feedback Speed Controller for Turbocharged Diesel Engine and Its Robustness
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.
A New Proportional - Pursuit Coupled Guidance Law with Actuator Delay Compensation
The aim of this paper is to present a new
three-dimensional proportional-pursuit coupled (PP) guidance law to
track highly maneuverable aircraft. Utilizing a 3-D polar coordinate frame, the PP guidance law is formed by collecting proportional
navigation guidance in Z-R plane and pursuit guidance in X-Y plane.
Feedback linearization control method to solve the guidance
accelerations is used to implement PP guidance. In order to
compensate the actuator time delay, the time delay compensated
version of PP guidance law (CPP) was derived and proved the
effectiveness of modifying the problem of high acceleration in the final
phase of pursuit guidance and improving the weak robustness of
proportional navigation. The simulation results for intercepting Max G
turn situation show that the proposed proportional-pursuit coupled
guidance law guidance law with actuator delay compensation (CPP)
possesses satisfactory robustness and performance.
Nonlinear Controller Design for Active Front Steering System
Active Front Steering system (AFS) provides an electronically controlled superposition of an angle to the steering wheel angle. This additional degree of freedom enables a continuous and driving-situation dependent on adaptation of the steering characteristics. In an active steering system, there needs be no fixed relationship between the steering wheel and the angle of the road wheels. Not only can the effective steering ratio be varied with speed, for example, but also the road wheel angles can be controlled by a combination of driver and computer inputs. Features like steering comfort, effort and steering dynamics are optimized and stabilizing steering interventions can be performed. In contrast to the conventional stability control, the yaw rate was fed back to AFS controller and the stability performance was optimized with Sliding Mode control (SMC) method. In addition, tire uncertainties have been taken into account in SM controller to provide the control robustness. In this paper, 3-DOF nonlinear model is used to design the AFS controller and 8-DOF nonlinear model is used to model the controlled vehicle.
The Fundamental Reliance of Iterative Learning Control on Stability Robustness
Iterative learning control aims to achieve zero tracking
error of a specific command. This is accomplished by iteratively
adjusting the command given to a feedback control system, based on
the tracking error observed in the previous iteration. One would like
the iterations to converge to zero tracking error in spite of any error
present in the model used to design the learning law. First, this need
for stability robustness is discussed, and then the need for robustness
of the property that the transients are well behaved. Methods of
producing the needed robustness to parameter variations and to
singular perturbations are presented. Then a method involving
reverse time runs is given that lets the world behavior produce the
ILC gains in such a way as to eliminate the need for a mathematical
model. Since the real world is producing the gains, there is no issue
of model error. Provided the world behaves linearly, the approach
gives an ILC law with both stability robustness and good transient
robustness, without the need to generate a model.
Design of Adaptive Sliding Mode Controller for Robotic Manipulators Tracking Control
This paper proposes an adaptive sliding mode
controller which combines adaptive control and sliding
mode control to control a nonlinear robotic manipulator
with uncertain parameters. We use an adaptive algorithm
based on the concept of sliding mode control to alleviate the
chattering phenomenon of control input. Adaptive laws are
developed to obtain the gain of switching input and the
boundary layer parameters. The stability and convergence
of the robotic manipulator control system are guaranteed
by applying the Lyapunov theorem. Simulation results
demonstrate that the chattering of control input can be
alleviated effectively. The proposed controller scheme can
assure robustness against a large class of uncertainties and
achieve good trajectory tracking performance.
Implementation of an Innovative Simplified Sliding Mode Observer-Based Robust Fault Detection in a Drum Boiler System
One of the robust fault detection filter (RFDF)
designing method is based on sliding-mode theory. The main purpose
of our study is to introduce an innovative simplified reference
residual model generator to formulate the RFDF as a sliding-mode
observer without any manipulation package or transformation matrix,
through which the generated residual signals can be evaluated. So the
proposed design is more explicit and requires less design parameters
in comparison with approaches requiring changing coordinates. To
the best author's knowledge, this is the first time that the sliding
mode technique is applied to detect actuator and sensor faults in a
real boiler. The designing procedure is proposed in a drum boiler in
Synvendska Kraft AB Plant in Malmo, Sweden as a multivariable
and strongly coupled system. It is demonstrated that both sensor and
actuator faults can robustly be detected. Also sensor faults can be
diagnosed and isolated through this method.
Alternative to M-Estimates in Multisensor Data Fusion
To solve the problem of multisensor data fusion under
non-Gaussian channel noise. The advanced M-estimates are known
to be robust solution while trading off some accuracy. In order to
improve the estimation accuracy while still maintaining the equivalent
robustness, a two-stage robust fusion algorithm is proposed using
preliminary rejection of outliers then an optimal linear fusion. The
numerical experiments show that the proposed algorithm is equivalent
to the M-estimates in the case of uncorrelated local estimates and
significantly outperforms the M-estimates when local estimates are
A Wavelet Based Object Watermarking System for Image and Video
Efficient storage, transmission and use of video information are key requirements in many multimedia applications currently being addressed by MPEG-4. To fulfill these requirements, a new approach for representing video information which relies on an object-based representation, has been adopted. Therefore, objectbased watermarking schemes are needed for copyright protection. This paper proposes a novel blind object watermarking scheme for images and video using the in place lifting shape adaptive-discrete wavelet transform (SA-DWT). In order to make the watermark robust and transparent, the watermark is embedded in the average of wavelet blocks using the visual model based on the human visual system. Wavelet coefficients n least significant bits (LSBs) are adjusted in concert with the average. Simulation results shows that the proposed watermarking scheme is perceptually invisible and robust against many attacks such as lossy image/video compression (e.g. JPEG, JPEG2000 and MPEG-4), scaling, adding noise, filtering, etc.
A Feature-based Invariant Watermarking Scheme Using Zernike Moments
In this paper, a novel feature-based image
watermarking scheme is proposed. Zernike moments which have
invariance properties are adopted in the scheme. In the proposed
scheme, feature points are first extracted from host image and several
circular patches centered on these points are generated. The patches
are used as carriers of watermark information because they can be
regenerated to locate watermark embedding positions even when
watermarked images are severely distorted. Zernike transform is then
applied to the patches to calculate local Zernike moments. Dither
modulation is adopted to quantize the magnitudes of the Zernike
moments followed by false alarm analysis. Experimental results show
that quality degradation of watermarked image is visually
transparent. The proposed scheme is very robust against image
processing operations and geometric attacks.
Text-independent Speaker Identification Based on MAP Channel Compensation and Pitch-dependent Features
One major source of performance decline in speaker
recognition system is channel mismatch between training and testing.
This paper focuses on improving channel robustness of speaker
recognition system in two aspects of channel compensation technique
and channel robust features. The system is text-independent speaker
identification system based on two-stage recognition. In the aspect of
channel compensation technique, this paper applies MAP (Maximum
A Posterior Probability) channel compensation technique, which was
used in speech recognition, to speaker recognition system. In the
aspect of channel robust features, this paper introduces
pitch-dependent features and pitch-dependent speaker model for the
second stage recognition. Based on the first stage recognition to
testing speech using GMM (Gaussian Mixture Model), the system
uses GMM scores to decide if it needs to be recognized again. If it
needs to, the system selects a few speakers from all of the speakers
who participate in the first stage recognition for the second stage
recognition. For each selected speaker, the system obtains 3
pitch-dependent results from his pitch-dependent speaker model, and
then uses ANN (Artificial Neural Network) to unite the 3
pitch-dependent results and 1 GMM score for getting a fused result.
The system makes the second stage recognition based on these fused
results. The experiments show that the correct rate of two-stage
recognition system based on MAP channel compensation technique
and pitch-dependent features is 41.7% better than the baseline system
for closed-set test.
Audio Watermarking Based on Compression-expansion Technique
A novel robust audio watermarking scheme is
proposed in this paper. In the proposed scheme, the host audio signals
are segmented into frames. Two consecutive frames are assessed if
they are suitable to represent a watermark bit. If so, frequency
transform is performed on these two frames. The compressionexpansion
technique is adopted to generate distortion over the two
frames. The distortion is used to represent one watermark bit.
Psychoacoustic model is applied to calculate local auditory mask to
ensure that the distortion is not audible. The watermarking schemes
using mono and stereo audio signals are designed differently. The
correlation-based detection method is used to detect the distortion
and extract embedded watermark bits. The experimental results show
that the quality degradation caused by the embedded watermarks is
perceptually transparent and the proposed schemes are very robust
against different types of attacks.
A Normalization-based Robust Image Watermarking Scheme Using SVD and DCT
Digital watermarking is one of the techniques for
copyright protection. In this paper, a normalization-based robust
image watermarking scheme which encompasses singular value
decomposition (SVD) and discrete cosine transform (DCT)
techniques is proposed. For the proposed scheme, the host image is
first normalized to a standard form and divided into non-overlapping
image blocks. SVD is applied to each block. By concatenating the
first singular values (SV) of adjacent blocks of the normalized image,
a SV block is obtained. DCT is then carried out on the SV blocks to
produce SVD-DCT blocks. A watermark bit is embedded in the highfrequency
band of a SVD-DCT block by imposing a particular
relationship between two pseudo-randomly selected DCT
coefficients. An adaptive frequency mask is used to adjust local
watermark embedding strength. Watermark extraction involves
mainly the inverse process. The watermark extracting method is blind
and efficient. Experimental results show that the quality degradation
of watermarked image caused by the embedded watermark is visually
transparent. Results also show that the proposed scheme is robust
against various image processing operations and geometric attacks.
A Normalization-based Robust Watermarking Scheme Using Zernike Moments
Digital watermarking has become an important technique for copyright protection but its robustness against attacks remains a major problem. In this paper, we propose a normalizationbased robust image watermarking scheme. In the proposed scheme, original host image is first normalized to a standard form. Zernike transform is then applied to the normalized image to calculate Zernike moments. Dither modulation is adopted to quantize the magnitudes of Zernike moments according to the watermark bit stream. The watermark extracting method is a blind method. Security analysis and false alarm analysis are then performed. The quality degradation of watermarked image caused by the embedded watermark is visually transparent. Experimental results show that the proposed scheme has very high robustness against various image processing operations and geometric attacks.
Simulation and Optimization of Mechanisms made of Micro-molded Components
The Institute of Product Development is dealing
with the development, design and dimensioning of micro components
and systems as a member of the Collaborative Research
Centre 499 “Design, Production and Quality Assurance of
Molded micro components made of Metallic and Ceramic Materials".
Because of technological restrictions in the miniaturization
of conventional manufacturing techniques, shape and
material deviations cannot be scaled down in the same proportion
as the micro parts, rendering components with relatively
wide tolerance fields. Systems that include such components
should be designed with this particularity in mind, often requiring
large clearance. On the end, the output of such systems
results variable and prone to dynamical instability. To save
production time and resources, every study of these effects
should happen early in the product development process and
base on computer simulation to avoid costly prototypes. A
suitable method is proposed here and exemplary applied to a
micro technology demonstrator developed by the CRC499. It
consists of a one stage planetary gear train in a sun-planet-ring
configuration, with input through the sun gear and output
through the carrier. The simulation procedure relies on ordinary
Multi Body Simulation methods and subsequently adds
other techniques to further investigate details of the system-s
behavior and to predict its response. The selection of the relevant
parameters and output functions followed the engineering
standards for regular sized gear trains. The first step is to
quantify the variability and to reveal the most critical points of
the system, performed through a whole-mechanism Sensitivity
Analysis. Due to the lack of previous knowledge about the system-s
behavior, different DOE methods involving small and
large amount of experiments were selected to perform the SA.
In this particular case the parameter space can be divided into
two well defined groups, one of them containing the gear-s profile
information and the other the components- spatial location.
This has been exploited to explore the different DOE techniques
more promptly. A reduced set of parameters is derived for
further investigation and to feed the final optimization process,
whether as optimization parameters or as external perturbation
collective. The 10 most relevant perturbation factors and 4 to 6
prospective variable parameters are considered in a new, simplified
model. All of the parameters are affected by the mentioned
production variability. The objective functions of interest
are based on scalar output-s variability measures, so the
problem becomes an optimization under robustness and reliability constrains. The study shows an initial step on the development
path of a method to design and optimize complex micro
mechanisms composed of wide tolerated elements accounting
for the robustness and reliability of the systems- output.
On Two Control Approaches for The Output Voltage Regulation of a Boost Converter
This paper deals with the comparison between two proposed control strategies for a DC-DC boost converter. The first control is a classical Sliding Mode Control (SMC) and the second one is a distance based Fuzzy Sliding Mode Control (FSMC). The SMC is an analytical control approach based on the boost mathematical model. However, the FSMC is a non-conventional control approach which does not need the controlled system mathematical model. It needs only the measures of the output voltage to perform the control signal. The obtained simulation results show that the two proposed control methods are robust for the case of load resistance and the input voltage variations. However, the proposed FSMC gives a better step voltage response than the one obtained by the SMC.
A Novel Digital Watermarking Technique Basedon ISB (Intermediate Significant Bit)
Least Significant Bit (LSB) technique is the earliest
developed technique in watermarking and it is also the most simple,
direct and common technique. It essentially involves embedding the
watermark by replacing the least significant bit of the image data with
a bit of the watermark data. The disadvantage of LSB is that it is not
robust against attacks. In this study intermediate significant bit (ISB)
has been used in order to improve the robustness of the watermarking
system. The aim of this model is to replace the watermarked image
pixels by new pixels that can protect the watermark data against
attacks and at the same time keeping the new pixels very close to the
original pixels in order to protect the quality of watermarked image.
The technique is based on testing the value of the watermark pixel
according to the range of each bit-plane.
Chattering Phenomenon Supression of Buck Boost DC-DC Converter with Fuzzy Sliding Modes Control
This paper proposes a Fuzzy Sliding Mode Control (FSMC) as a control strategy for Buck-Boost DC-DC converter. The proposed fuzzy controller specifies changes in the control signal based on the knowledge of the surface and the surface change to satisfy the sliding mode stability and attraction conditions. The performances of the proposed fuzzy sliding controller are compared to those obtained by a classical sliding mode controller. The satisfactory simulation results show the efficiency of the proposed control law which reduces the chattering phenomenon. Moreover, the obtained results prove the robustness of the proposed control law against variation of the load resistance and the input voltage of the studied converter.
Fuzzy Logic Approach to Robust Regression Models of Uncertain Medical Categories
Dichotomization of the outcome by a single cut-off point is an important part of various medical studies. Usually the relationship between the resulted dichotomized dependent variable and explanatory variables is analyzed with linear regression, probit regression or logistic regression. However, in many real-life situations, a certain cut-off point dividing the outcome into two groups is unknown and can be specified only approximately, i.e. surrounded by some (small) uncertainty. It means that in order to have any practical meaning the regression model must be robust to this uncertainty. In this paper, we show that neither the beta in the linear regression model, nor its significance level is robust to the small variations in the dichotomization cut-off point. As an alternative robust approach to the problem of uncertain medical categories, we propose to use the linear regression model with the fuzzy membership function as a dependent variable. This fuzzy membership function denotes to what degree the value of the underlying (continuous) outcome falls below or above the dichotomization cut-off point. In the paper, we demonstrate that the linear regression model of the fuzzy dependent variable can be insensitive against the uncertainty in the cut-off point location. In the paper we present the modeling results from the real study of low hemoglobin levels in infants. We systematically test the robustness of the binomial regression model and the linear regression model with the fuzzy dependent variable by changing the boundary for the category Anemia and show that the behavior of the latter model persists over a quite wide interval.
Mimicking Morphogenesis for Robust Behaviour of Cellular Architectures
Morphogenesis is the process that underpins the selforganised development and regeneration of biological systems. The ability to mimick morphogenesis in artificial systems has great potential for many engineering applications, including production of biological tissue, design of robust electronic systems and the co-ordination of parallel computing. Previous attempts to mimick these complex dynamics within artificial systems have relied upon the use of evolutionary algorithms that have limited their size and complexity. This paper will present some insight into the underlying dynamics of morphogenesis, then show how to, without the assistance of evolutionary algorithms, design cellular architectures that converge to complex patterns.