Abstract: In this paper we present a soft timing phase estimation (STPE) method for wireless mobile receivers operating in low signal to noise ratios (SNRs). Discrete Polyphase Matched (DPM) filters, a Log-maximum a posterior probability (MAP) and/or a Soft-output Viterbi algorithm (SOVA) are combined to derive a new timing recovery (TR) scheme. We apply this scheme to wireless cellular communication system model that comprises of a raised cosine filter (RCF), a bit-interleaved turbo-coded multi-level modulation (BITMM) scheme and the channel is assumed to be memory-less. Furthermore, no clock signals are transmitted to the receiver contrary to the classical data aided (DA) models. This new model ensures that both the bandwidth and power of the communication system is conserved. However, the computational complexity of ideal turbo synchronization is increased by 50%. Several simulation tests on bit error rate (BER) and block error rate (BLER) versus low SNR reveal that the proposed iterative soft timing recovery (ISTR) scheme outperforms the conventional schemes.
Abstract: This paper uses the radial basis function neural
network (RBFNN) for system identification of nonlinear systems.
Five nonlinear systems are used to examine the activity of RBFNN in
system modeling of nonlinear systems; the five nonlinear systems are
dual tank system, single tank system, DC motor system, and two
academic models. The feed forward method is considered in this
work for modelling the non-linear dynamic models, where the KMeans
clustering algorithm used in this paper to select the centers of
radial basis function network, because it is reliable, offers fast
convergence and can handle large data sets. The least mean square
method is used to adjust the weights to the output layer, and
Euclidean distance method used to measure the width of the Gaussian
function.
Abstract: The impact of fixed speed squirrel cage type as well as
variable speed doubly fed induction generators (DFIG) on dynamic
performance of a multimachine power system has been investigated.
Detailed models of the various components have been presented and
the integration of asynchronous and synchronous generators has been
carried out through a rotor angle based transform. Simulation studies
carried out considering the conventional dynamic model of squirrel
cage asynchronous generators show that integration, as such, could
degrade to the AC system performance transiently. This article
proposes a frequency or power controller which can effectively
control the transients and restore normal operation of fixed speed
induction generator quickly. Comparison of simulation results
between classical cage and doubly-fed induction generators indicate
that the doubly fed induction machine is more adaptable to
multimachine AC system. Frequency controller installed in the DFIG
system can also improve its transient profile.
Abstract: The first generation of Mobile Agents based Intrusion
Detection System just had two components namely data collection
and single centralized analyzer. The disadvantage of this type of
intrusion detection is if connection to the analyzer fails, the entire
system will become useless. In this work, we propose novel hybrid
model for Mobile Agent based Distributed Intrusion Detection
System to overcome the current problem. The proposed model has
new features such as robustness, capability of detecting intrusion
against the IDS itself and capability of updating itself to detect new
pattern of intrusions. In addition, our proposed model is also capable
of tackling some of the weaknesses of centralized Intrusion Detection
System models.
Abstract: In this paper, we are interested in attitude control of a satellite, which using wheels of reaction, by state feedback. First, we develop a method allowing us to put the control and its integral in the state-feedback form. Then, by using the theorem of Gronwall- Bellman, we put the sufficient conditions so that the nonlinear system modeling the satellite is stabilisable and observed by state feedback.
Abstract: In a product development process, understanding the functional behavior of the system, the role of components in achieving functions and failure modes if components/subsystem fails its required function will help develop appropriate design validation and verification program for reliability assessment. The integration of these three issues will help design and reliability engineers in identifying weak spots in design and planning future actions and testing program. This case study demonstrate the advantage of unascertained theory described in the subjective cognition uncertainty, and then applies blind number (BN) theory in describing the uncertainty of the mechanical system failure process and the same time used the same theory in bringing out another mechanical reliability system model. The practical calculations shows the BN Model embodied the characters of simply, small account of calculation but betterforecasting capability, which had the value of macroscopic discussion to some extent.
Abstract: This paper considers the influence of promotion
instruments for renewable energy sources (RES) on a multi-energy
modeling framework. In Europe, so called Feed-in Tariffs are
successfully used as incentive structures to increase the amount of
energy produced by RES. Because of the stochastic nature of large
scale integration of distributed generation, many problems have
occurred regarding the quality and stability of supply. Hence, a
macroscopic model was developed in order to optimize the power
supply of the local energy infrastructure, which includes electricity,
natural gas, fuel oil and district heating as energy carriers. Unique
features of the model are the integration of RES and the adoption of
Feed-in Tariffs into one optimization stage. Sensitivity studies are
carried out to examine the system behavior under changing profits
for the feed-in of RES. With a setup of three energy exchanging
regions and a multi-period optimization, the impact of costs and
profits are determined.
Abstract: In this paper, investigation of subsynchronous
resonance (SSR) characteristics of a hybrid series compensated
system and the design of voltage controller for three level 24-pulse
Voltage Source Converter based Static Synchronous Series
Compensator (SSSC) is presented. Hybrid compensation consists of
series fixed capacitor and SSSC which is a active series FACTS
controller. The design of voltage controller for SSSC is based on
damping torque analysis, and Genetic Algorithm (GA) is adopted for
tuning the controller parameters. The SSR Characteristics of SSSC
with constant reactive voltage control modes has been investigated.
The results show that the constant reactive voltage control of SSSC
has the effect of reducing the electrical resonance frequency, which
detunes the SSR.The analysis of SSR with SSSC is carried out based
on frequency domain method, eigenvalue analysis and transient
simulation. While the eigenvalue and damping torque analysis are
based on D-Q model of SSSC, the transient simulation considers both
D-Q and detailed three phase nonlinear system model using
switching functions.
Abstract: In this paper, an analysis of a target location estimation
system using the best linear unbiased estimator (BLUE) for high
performance radar systems is presented. In synthetic environments,
we are here concerned with three key elements of radar system
modeling, which makes radar systems operates accurately in strategic
situation in virtual ground. Radar Cross Section (RCS) modeling
is used to determine the actual amount of electromagnetic waves
that are reflected from a tactical object. Pattern Propagation Factor
(PPF) is an attenuation coefficient of the radar equation that contains
the reflection from the surface of the earth, the diffraction, the
refraction and scattering by the atmospheric environment. Clutter is
the unwanted echoes of electronic systems. For the data fusion of
output results from radar detection in synthetic environment, BLUE
is used and compared with the mean values of each simulation results.
Simulation results demonstrate the performance of the radar system.
Abstract: This paper describes the optimization of a complex
dairy farm simulation model using two quite different methods of
optimization, the Genetic algorithm (GA) and the Lipschitz
Branch-and-Bound (LBB) algorithm. These techniques have been
used to improve an agricultural system model developed by Dexcel
Limited, New Zealand, which describes a detailed representation of
pastoral dairying scenarios and contains an 8-dimensional parameter
space. The model incorporates the sub-models of pasture growth and
animal metabolism, which are themselves complex in many cases.
Each evaluation of the objective function, a composite 'Farm
Performance Index (FPI)', requires simulation of at least a one-year
period of farm operation with a daily time-step, and is therefore
computationally expensive. The problem of visualization of the
objective function (response surface) in high-dimensional spaces is
also considered in the context of the farm optimization problem.
Adaptations of the sammon mapping and parallel coordinates
visualization are described which help visualize some important
properties of the model-s output topography. From this study, it is
found that GA requires fewer function evaluations in optimization
than the LBB algorithm.
Abstract: Software testing is important stage of software development cycle. Current testing process involves tester and electronic documents with test case scenarios. In this paper we focus on new approach to testing process using automated test case generation and tester guidance through the system based on the model of the system. Test case generation and model-based testing is not possible without proper system model. We aim on providing better feedback from the testing process thus eliminating the unnecessary paper work.
Abstract: This paper presents a unified approach based graph
theory and system theory postulates for the modeling and analysis
of Simple open cycle Gas turbine system. In the present paper, the
simple open cycle gas turbine system has been modeled up to its subsystem
level and system variables have been identified to develop the
process subgraphs. The theorems and algorithms of the graph theory
have been used to represent behavioural properties of the system like
rate of heat and work transfers rates, pressure drops and temperature
drops in the involved processes of the system. The processes have
been represented as edges of the process subgraphs and their limits
as the vertices of the process subgraphs. The system across variables
and through variables has been used to develop terminal equations of
the process subgraphs of the system. The set of equations developed
for vertices and edges of network graph are used to solve the system
for its process variables.