Abstract: DC motors have been widely used in the past
centuries which are proudly known as the workhorse of industrial
systems until the invention of the AC induction motors which makes
a huge revolution in industries. Since then, the use of DC machines
has been decreased due to enormous factors such as reliability,
robustness and complexity but it lost its fame due to the losses. In this
paper a new methodology is proposed to construct a DC motor
through the simulation in LabVIEW to get an idea about its real time
performances, if a change in parameter might have bigger
improvement in losses and reliability.
Abstract: Micro-electromechanical system (MEMS)
accelerometers and gyroscopes are suitable for the inertial navigation
system (INS) of many applications due to low price, small
dimensions and light weight. The main disadvantage in a comparison
with classic sensors is a worse long term stability. The estimation
accuracy is mostly affected by the time-dependent growth of inertial
sensor errors, especially the stochastic errors. In order to eliminate
negative effects of these random errors, they must be accurately
modeled. In this paper, the Allan variance technique will be used in
modeling the stochastic errors of the inertial sensors. By performing
a simple operation on the entire length of data, a characteristic curve
is obtained whose inspection provides a systematic characterization
of various random errors contained in the inertial-sensor output data.
Abstract: In this study, we proposed two techniques to track the
maximum power point (MPPT) of a photovoltaic system. The first is
an intelligent control technique, and the second is robust used for
variable structure system. In fact the characteristics I-V and P–V of
the photovoltaic generator depends on the solar irradiance and
temperature. These climate changes cause the fluctuation of
maximum power point; a maximum power point tracking technique
(MPPT) is required to maximize the output power. For this we have
adopted a control by fuzzy logic (FLC) famous for its stability and
robustness. And a Siding Mode Control (SMC) widely used for
variable structure system. The system comprises a photovoltaic panel
(PV), a DC-DC converter, which is considered as an adaptation stage
between the PV and the load. The modelling and simulation of the
system is developed using MATLAB/Simulink. SMC technique
provides a good tracking speed in fast changing irradiation and when
the irradiation changes slowly or it is constant the panel power of
FLC technique presents a much smoother signal with less
fluctuations.
Abstract: A simple adaptive voice activity detector (VAD) is
implemented using Gabor and gammatone atomic decomposition of
speech for high Gaussian noise environments. Matching pursuit is
used for atomic decomposition, and is shown to achieve optimal
speech detection capability at high data compression rates for low
signal to noise ratios. The most active dictionary elements found by
matching pursuit are used for the signal reconstruction so that the
algorithm adapts to the individual speakers dominant time-frequency
characteristics. Speech has a high peak to average ratio enabling
matching pursuit greedy heuristic of highest inner products to isolate
high energy speech components in high noise environments. Gabor
and gammatone atoms are both investigated with identical
logarithmically spaced center frequencies, and similar bandwidths.
The algorithm performs equally well for both Gabor and gammatone
atoms with no significant statistical differences. The algorithm
achieves 70% accuracy at a 0 dB SNR, 90% accuracy at a 5 dB SNR
and 98% accuracy at a 20dB SNR using 30d B SNR as a reference
for voice activity.
Abstract: Due to the continuous increment of the load demand,
identification of weaker buses, improvement of voltage profile and
power losses in the context of the voltage stability problems has
become one of the major concerns for the larger, complex,
interconnected power systems. The objective of this paper is to
review the impact of Flexible AC Transmission System (FACTS)
controller in Wind generators connected electrical network for
maintaining voltage stability. Wind energy could be the growing
renewable energy due to several advantages. The influence of wind
generators on power quality is a significant issue; non uniform power
production causes variations in system voltage and frequency.
Therefore, wind farm requires high reactive power compensation; the
advances in high power semiconducting devices have led to the
development of FACTS. The FACTS devices such as for example
SVC inject reactive power into the system which helps in maintaining
a better voltage profile. The performance is evaluated on an IEEE 14
bus system, two wind generators are connected at low voltage buses
to meet the increased load demand and SVC devices are integrated at
the buses with wind generators to keep voltage stability. Power
flows, nodal voltage magnitudes and angles of the power network are
obtained by iterative solutions using MIPOWER.
Abstract: This article presents two methods for the
compensation of harmonics generated by a nonlinear load. The first is
the classic method P-Q. The second is the controller by modern
method of artificial intelligence specifically fuzzy logic. Both
methods are applied to a shunt Active Power Filter (sAPF) based on a
three-phase voltage converter at five levels NPC topology. In
calculating the harmonic currents of reference, we use the algorithm
P-Q and pulse generation, we use the intersective PWM. For
flexibility and dynamics, we use fuzzy logic. The results give us clear
that the rate of Harmonic Distortion issued by fuzzy logic is better
than P-Q.
Abstract: We present a refined multiscale Shannon entropy for
analyzing electroencephalogram (EEG), which reflects the underlying
dynamics of EEG over multiple scales. The rationale behind
this method is that neurological signals such as EEG possess
distinct dynamics over different spectral modes. To deal with the
nonlinear and nonstationary nature of EEG, the recently developed
empirical mode decomposition (EMD) is incorporated, allowing a
decomposition of EEG into its inherent spectral components, referred
to as intrinsic mode functions (IMFs). By calculating the Shannon
entropy of IMFs in a time-dependent manner and summing them over
adaptive multiple scales, it results in an adaptive subscale entropy
measure of EEG. Simulation and experimental results show that
the proposed entropy properly reveals the dynamical changes over
multiple scales.
Abstract: This paper describes an optimization tool-based
design strategy for a Current Mode Logic CML divide-by-2 circuit.
Representing a building block for output frequency generation in a
RFID protocol based-frequency synthesizer, the circuit was designed
to minimize the power consumption for driving of multiple loads
with unbalancing (at transceiver level). Implemented with XFAB
XC08 180 nm technology, the circuit was optimized through
MunEDA WiCkeD tool at Cadence Virtuoso Analog Design
Environment ADE.
Abstract: In a practical power system, the power plants are not
located at the same distance from the center of loads and their fuel
costs are different. Also, under normal operating conditions, the
generation capacity is more than the total load demand and losses.
Thus, there are many options for scheduling generation. In an
interconnected power system, the objective is to find the real and
reactive power scheduling of each power plant in such a way as to
minimize the operating cost. This means that the generator’s real and
reactive powers are allowed to vary within certain limits so as to meet
a particular load demand with minimum fuel cost. This is called
optimal power flow problem. In this paper, Economic Load Dispatch
(ELD) of real power generation is considered. Economic Load
Dispatch (ELD) is the scheduling of generators to minimize total
operating cost of generator units subjected to equality constraint of
power balance within the minimum and maximum operating limits of
the generating units. In this paper, genetic algorithms are considered.
ELD solutions are found by solving the conventional load flow
equations while at the same time minimizing the fuel costs.
Abstract: This paper presents an optimization method for
reducing the number of input channels and the complexity of the
feed-forward NARX neural network (NN) without compromising the
accuracy of the NN model. By utilizing the correlation analysis
method, the most significant regressors are selected to form the input
layer of the NN structure. An application of vehicle dynamic model
identification is also presented in this paper to demonstrate the
optimization technique and the optimal input layer structure and the
optimal number of neurons for the neural network is investigated.
Abstract: A novel design technique employing CMOS Current
Feedback Operational Amplifier (CFOA) is presented. The feature of
consumption very low power in designing pseudo-OTA is used to
decreasing the total power consumption of the proposed CFOA. This
design approach applies pseudo-OTA as input stage cascaded with
buffer stage. Moreover, the DC input offset voltage and harmonic
distortion (HD) of the proposed CFOA are very low values compared
with the conventional CMOS CFOA due to the symmetrical input
stage. P-Spice simulation results are obtained using 0.18μm MIETEC
CMOS process parameters and supply voltage of ±1.2V, 50μA
biasing current. The p-spice simulation shows excellent improvement
of the proposed CFOA over existing CMOS CFOA. Some of these
performance parameters, for example, are DC gain of 62. dB, openloop
gain bandwidth product of 108 MHz, slew rate (SR+) of
+71.2V/μS, THD of -63dB and DC consumption power (PC) of
2mW.
Abstract: Fast speed drives for Permanent Magnet Synchronous
Motor (PMSM) is a crucial performance for the electric traction
systems. In this paper, PMSM is derived with a Model-based
Predictive Control (MPC) technique. Fast speed tracking is achieved
through optimization of the DC source utilization using MPC. The
technique is based on predicting the optimum voltage vector applied
to the driver. Control technique is investigated by comparing to the
cascaded PI control based on Space Vector Pulse Width Modulation
(SVPWM). MPC and SVPWM-based FOC are implemented with the
TMS320F2812 DSP and its power driver circuits. The designed MPC
for a PMSM drive is experimentally validated on a laboratory test
bench. The performances are compared with those obtained by a
conventional PI-based system in order to highlight the improvements,
especially regarding speed tracking response.
Abstract: A compound parabolic concentrator (CPC) is a wellknown
non-imaging concentrator that will concentrate the solar
radiation onto receiver (PV cell). One of disadvantage of CPC is has
tall and narrow height compared to its diameter entry aperture area.
Therefore, for economic reason, a truncation had been done by
removed from the top of the full height CPC. This also will lead to
the decreases of concentration ratio but it will be negligible. In this
paper, the flux distribution of untruncated and truncated 2-D hollow
compound parabolic trough concentrator (hCPTC) design is
presented. The untruncated design has initial height H=193.4mm
with concentration ratio C_(2-D)=4. This paper presents the optical
simulation of compound parabolic trough concentrator using raytracing
software TracePro. Results showed that, after the truncation,
the height of CPC reduced 45% from initial height with the
geometrical concentration ratio only decrease 10%. Thus, the cost of
reflector and material dielectric usage can be saved especially at
manufacturing site.
Abstract: This study examines the feasibility of indirect solar
desalination in oil producing countries in the Middle East and North
Africa (MENA) region. It relies on value engineering (VE) and costbenefit
with sensitivity analyses to identify optimal coupling
configurations of desalination and solar energy technologies. A
comparative return on investment was assessed as a function of water
costs for varied plant capacities (25,000 to 75,000 m3/day), project
lifetimes (15 to 25 years), and discount rates (5 to 15%) taking into
consideration water and energy subsidies, land cost as well as
environmental externalities in the form of carbon credit related to
greenhouse gas (GHG) emissions reduction. The results showed
reverse osmosis (RO) coupled with photovoltaic technologies (PVs)
as the most promising configuration, robust across different prices for
Brent oil, discount rates, as well as different project lifetimes.
Environmental externalities and subsidies analysis revealed that a
16% reduction in existing subsidy on water tariffs would ensure
economic viability. Additionally, while land costs affect investment
attractiveness, the viability of RO coupled with PV remains possible
for a land purchase cost
Abstract: To explore how the brain may recognise objects in its
general,accurate and energy-efficient manner, this paper proposes the
use of a neuromorphic hardware system formed from a Dynamic
Video Sensor (DVS) silicon retina in concert with the SpiNNaker
real-time Spiking Neural Network (SNN) simulator. As a first step
in the exploration on this platform a recognition system for dynamic
hand postures is developed, enabling the study of the methods used
in the visual pathways of the brain. Inspired by the behaviours of
the primary visual cortex, Convolutional Neural Networks (CNNs)
are modelled using both linear perceptrons and spiking Leaky
Integrate-and-Fire (LIF) neurons.
In this study’s largest configuration using these approaches, a
network of 74,210 neurons and 15,216,512 synapses is created and
operated in real-time using 290 SpiNNaker processor cores in parallel
and with 93.0% accuracy. A smaller network using only 1/10th of the
resources is also created, again operating in real-time, and it is able
to recognise the postures with an accuracy of around 86.4% - only
6.6% lower than the much larger system. The recognition rate of the
smaller network developed on this neuromorphic system is sufficient
for a successful hand posture recognition system, and demonstrates
a much improved cost to performance trade-off in its approach.
Abstract: Nowadays, the use of renewable energy sources has been increasingly great because of the cost increase and public demand for clean energy sources. One of the fastest growing sources is wind energy. In this paper, Wind Diesel Hybrid System (WDHS) comprising a Diesel Generator (DG), a Wind Turbine Generator (WTG), the Consumer Load, a Battery-based Energy Storage System (BESS), and a Dump Load (DL) is used. Voltage is controlled by Diesel Generator; the frequency is controlled by BESS and DL. The BESS elimination is an efficient way to reduce maintenance cost and increase the dynamic response. Simulation results with graphs for the frequency of Power System, active power, and the battery power are presented for load changes. The controlling parameters are optimized by using Imperialist Competitive Algorithm (ICA). The simulation results for the BESS/no BESS cases are compared. Results show that in no BESS case, the frequency control is more optimal than the BESS case by using ICA.
Abstract: We investigate experimentally and theoretically the
dynamics of a capacitive resonator under mixed frequency excitation
of two AC harmonic signals. The resonator is composed of a proof
mass suspended by two cantilever beams. Experimental
measurements are conducted using a laser Doppler Vibrometer to
reveal the interesting dynamics of the system when subjected to twosource
excitation. A nonlinear single-degree-of-freedom model is
used for the theoretical investigation. The results reveal combination
resonances of additive and subtractive type, which are shown to be
promising to increase the bandwidth of the resonator near primary
resonance frequency. Our results also demonstrate the ability to shift
the combination resonances to much lower or much higher frequency
ranges. We also demonstrate the dynamic pull-in instability under
mixed frequency excitation.
Abstract: This paper proposes a novel heuristic algorithm that aims to determine the best size and location of distributed generators in unbalanced distribution networks. The proposed heuristic algorithm can deal with the planning cases where power loss is to be optimized without violating the system practical constraints. The distributed generation units in the proposed algorithm is modeled as voltage controlled node with the flexibility to be converted to constant power factor node in case of reactive power limit violation. The proposed algorithm is implemented in MATLAB and tested on the IEEE 37 -node feeder. The results obtained show the effectiveness of the proposed algorithm.
Abstract: This paper proposed the comparison made between
Multi-Carrier Pulse Width Modulation, Sinusoidal Pulse Width
Modulation and Selective Harmonic Elimination Pulse Width
Modulation technique for minimization of Total Harmonic Distortion
in Cascaded H-Bridge Multi-Level Inverter. In Multicarrier Pulse
Width Modulation method by using Alternate Position of Disposition
scheme for switching pulse generation to Multi-Level Inverter.
Another carrier based approach; Sinusoidal Pulse Width Modulation
method is also implemented to define the switching pulse generation
system in the multi-level inverter. In Selective Harmonic Elimination
method using Genetic Algorithm and Particle Swarm Optimization
algorithm for define the required switching angles to eliminate low
order harmonics from the inverter output voltage waveform and
reduce the total harmonic distortion value. So, the results validate that
the Selective Harmonic Elimination Pulse Width Modulation method
does capably eliminate a great number of precise harmonics and
minimize the Total Harmonic Distortion value in output voltage
waveform in compared with Multi-Carrier Pulse Width Modulation
method, Sinusoidal Pulse Width Modulation method. In this paper,
comparison of simulation results shows that the Selective Harmonic
Elimination method can attain optimal harmonic minimization
solution better than Multi-Carrier Pulse Width Modulation method,
Sinusoidal Pulse Width Modulation method.
Abstract: Floorplanning plays a vital role in the physical design
process of Very Large Scale Integrated (VLSI) chips. It is an
essential design step to estimate the chip area prior to the optimized
placement of digital blocks and their interconnections. Since VLSI
floorplanning is an NP-hard problem, many optimization techniques
were adopted in the literature. In this work, a music-inspired
Harmony Search (HS) algorithm is used for the fixed die outline
constrained floorplanning, with the aim of reducing the total chip
area. HS draws inspiration from the musical improvisation process of
searching for a perfect state of harmony. Initially, B*-tree is used to
generate the primary floorplan for the given rectangular hard
modules and then HS algorithm is applied to obtain an optimal
solution for the efficient floorplan. The experimental results of the
HS algorithm are obtained for the MCNC benchmark circuits.