Abstract: In this paper we consider a nonlinear feedback control
called augmented automatic choosing control (AACC) using the
gradient optimization automatic choosing functions for nonlinear
systems. Constant terms which arise from sectionwise linearization
of a given nonlinear system are treated as coefficients of a stable
zero dynamics. Parameters included in the control are suboptimally
selected by expanding a stable region in the sense of Lyapunov
with the aid of the genetic algorithm. This approach is applied to
a field excitation control problem of power system to demonstrate
the splendidness of the AACC. Simulation results show that the new
controller can improve performance remarkably well.
Abstract: In this paper a new method is suggested for
distributed data-mining by the probability patterns. These patterns
use decision trees and decision graphs. The patterns are cared to be
valid, novel, useful, and understandable. Considering a set of
functions, the system reaches to a good pattern or better objectives.
By using the suggested method we will be able to extract the useful
information from massive and multi-relational data bases.
Abstract: We seek exact solutions of the coupled Klein-Gordon-Schrödinger equation with variable coefficients with the aid of Lie classical approach. By using the Lie classical method, we are able to derive symmetries that are used for reducing the coupled system of partial differential equations into ordinary differential equations. From reduced differential equations we have derived some new exact solutions of coupled Klein-Gordon-Schrödinger equations involving some special functions such as Airy wave functions, Bessel functions, Mathieu functions etc.
Abstract: Both the minimum energy consumption and
smoothness, which is quantified as a function of jerk, are generally
needed in many dynamic systems such as the automobile and the
pick-and-place robot manipulator that handles fragile equipments.
Nevertheless, many researchers come up with either solely
concerning on the minimum energy consumption or minimum jerk
trajectory. This research paper proposes a simple yet very interesting
when combining the minimum energy and jerk of indirect jerks
approaches in designing the time-dependent system yielding an
alternative optimal solution. Extremal solutions for the cost functions
of the minimum energy, the minimum jerk and combining them
together are found using the dynamic optimization methods together
with the numerical approximation. This is to allow us to simulate
and compare visually and statistically the time history of state inputs
employed by combining minimum energy and jerk designs. The
numerical solution of minimum direct jerk and energy problem are
exactly the same solution; however, the solutions from problem of
minimum energy yield the similar solution especially in term of
tendency.
Abstract: The statistical distributions are modeled in explaining
nature of various types of data sets. Although these distributions are
mostly uni-modal, it is quite common to see multiple modes in the
observed distribution of the underlying variables, which make the
precise modeling unrealistic. The observed data do not exhibit
smoothness not necessarily due to randomness, but could also be due
to non-randomness resulting in zigzag curves, oscillations, humps
etc. The present paper argues that trigonometric functions, which
have not been used in probability functions of distributions so far,
have the potential to take care of this, if incorporated in the
distribution appropriately. A simple distribution (named as, Sinoform
Distribution), involving trigonometric functions, is illustrated in the
paper with a data set. The importance of trigonometric functions is
demonstrated in the paper, which have the characteristics to make
statistical distributions exotic. It is possible to have multiple modes,
oscillations and zigzag curves in the density, which could be suitable
to explain the underlying nature of select data set.
Abstract: The unanticipated brittle fracture of connection of the
steel moment resisting frame (SMRF) occurred in 1994 the Northridge
earthquake. Since then, the researches for the vulnerability of
connection of the existing SMRF and for rehabilitation of those
buildings were conducted. This paper suggests performance-based
optimal seismic retrofit technique using connection upgrade. For
optimal design, a multi-objective genetic algorithm(NSGA-II) is used.
One of the two objective functions is to minimize initial cost and
another objective function is to minimize lifetime seismic damages
cost. The optimal algorithm proposed in this paper is performed
satisfying specified performance objective based on FEMA 356. The
nonlinear static analysis is performed for structural seismic
performance evaluation. A numerical example of SAC benchmark
SMRF is provided using the performance-based optimal seismic
retrofit technique proposed in this paper
Abstract: This research proposes a Preemptive Possibilistic
Linear Programming (PPLP) approach for solving multiobjective
Aggregate Production Planning (APP) problem with interval demand
and imprecise unit price and related operating costs. The proposed
approach attempts to maximize profit and minimize changes of
workforce. It transforms the total profit objective that has imprecise
information to three crisp objective functions, which are maximizing
the most possible value of profit, minimizing the risk of obtaining the
lower profit and maximizing the opportunity of obtaining the higher
profit. The change of workforce level objective is also converted.
Then, the problem is solved according to objective priorities. It is
easier than simultaneously solve the multiobjective problem as
performed in existing approach. Possible range of interval demand is
also used to increase flexibility of obtaining the better production
plan. A practical application of an electronic company is illustrated to
show the effectiveness of the proposed model.
Abstract: IMCS is Integrated Monitoring and Control System for
thermal power plant. This system consists of mainly two parts; controllers and OIS (Operator Interface System). These two parts are
connected by Ethernet-based communication. The controller side of communication is managed by CNet module and OIS side is managed
by data server of OIS. CNet module sends the data of controller to data
server and receives commend data from data server. To minimizes or
balance the load of data server, this module buffers data created by controller at every cycle and send buffered data to data server on request of data server. For multiple data server, this module manages
the connection line with each data server and response for each request
from multiple data server. CNet module is included in each controller
of redundant system. When controller fail-over happens on redundant system, this module can provide data of controller to data sever
without loss. This paper presents three main features – separation of get task, usage of ring buffer and monitoring communication status –of CNet module to carry out these functions.
Abstract: Biomimicry has many potential benefits as many
technologies found in nature are superior to their man-made
counterparts. As technological device components approach the micro
and nanoscale, surface properties such as surface adhesion and friction
may need to be taken into account. Lowering surface adhesion by
manipulating chemistry alone might no longer be sufficient for such
components and thus physical manipulation may be required.
Adhesion reduction is only one of the many surface functions
displayed by micro/nano-structured cuticles of insects. Here, we
present a mini review of our understanding of insect cuticle structures
and the relationship between the structure dimensions and the
corresponding functional mechanisms. It may be possible to introduce
additional properties to material surfaces (indeed multi-functional
properties) based on the design of natural surfaces.
Abstract: A hardware efficient, multi mode, re-configurable
architecture of interleaver/de-interleaver for multiple standards,
like DVB, WiMAX and WLAN is presented. The interleavers
consume a large part of silicon area when implemented by using
conventional methods as they use memories to store permutation
patterns. In addition, different types of interleavers in different
standards cannot share the hardware due to different construction
methodologies. The novelty of the work presented in this paper is
threefold: 1) Mapping of vital types of interleavers including
convolutional interleaver onto a single architecture with flexibility
to change interleaver size; 2) Hardware complexity for channel
interleaving in WiMAX is reduced by using 2-D realization of the
interleaver functions; and 3) Silicon cost overheads reduced by
avoiding the use of small memories. The proposed architecture
consumes 0.18mm2 silicon area for 0.12μm process and can
operate at a frequency of 140 MHz. The reduced complexity helps
in minimizing the memory utilization, and at the same time
provides strong support to on-the-fly computation of permutation
patterns.
Abstract: The demand of the energy management systems (EMS) set forth by modern power systems requires fast energy management systems. Contingency analysis is among the functions in EMS which is time consuming. In order to handle this limitation, this paper introduces agent based technology in the contingency analysis. The main function of agents is to speed up the performance. Negotiations process in decision making is explained and the issue set forth is the minimization of the operating costs. The IEEE 14 bus system and its line outage have been used in the research and simulation results are presented.
Abstract: Smoothing or filtering of data is first preprocessing step
for noise suppression in many applications involving data analysis.
Moving average is the most popular method of smoothing the data,
generalization of this led to the development of Savitzky-Golay filter.
Many window smoothing methods were developed by convolving
the data with different window functions for different applications;
most widely used window functions are Gaussian or Kaiser. Function
approximation of the data by polynomial regression or Fourier
expansion or wavelet expansion also gives a smoothed data. Wavelets
also smooth the data to great extent by thresholding the wavelet
coefficients. Almost all smoothing methods destroys the peaks and
flatten them when the support of the window is increased. In certain
applications it is desirable to retain peaks while smoothing the data
as much as possible. In this paper we present a methodology called
as peak-wise smoothing that will smooth the data to any desired level
without losing the major peak features.
Abstract: The computer has become an essential tool in modern
life, and the combined use of a computer with a projector is very
common in teaching and presentations. However, as typical computer
operating devices involve a mouse or keyboard, when making
presentations, users often need to stay near the computer to execute
functions such as changing pages, writing, and drawing, thus, making
the operation time-consuming, and reducing interactions with the
audience. This paper proposes a laser pointer interaction system able
to simulate mouse functions in order that users need not remain near
the computer, but can directly use laser pointer operations from at a
distance. It can effectively reduce the users- time spent by the
computer, allowing for greater interactions with the audience.
Abstract: This work explores blind image deconvolution by recursive function approximation based on supervised learning of neural networks, under the assumption that a degraded image is linear convolution of an original source image through a linear shift-invariant (LSI) blurring matrix. Supervised learning of neural networks of radial basis functions (RBF) is employed to construct an embedded recursive function within a blurring image, try to extract non-deterministic component of an original source image, and use them to estimate hyper parameters of a linear image degradation model. Based on the estimated blurring matrix, reconstruction of an original source image from a blurred image is further resolved by an annealed Hopfield neural network. By numerical simulations, the proposed novel method is shown effective for faithful estimation of an unknown blurring matrix and restoration of an original source image.
Abstract: Methods to detect and localize time singularities of polynomial and quasi-polynomial ordinary differential equations are systematically presented and developed. They are applied to examples taken form different fields of applications and they are also compared to better known methods such as those based on the existence of linear first integrals or Lyapunov functions.
Abstract: This paper deals with the tuning of parameters for Automatic Generation Control (AGC). A two area interconnected hydrothermal system with PI controller is considered. Genetic Algorithm (GA) and Particle Swarm optimization (PSO) algorithms have been applied to optimize the controller parameters. Two objective functions namely Integral Square Error (ISE) and Integral of Time-multiplied Absolute value of the Error (ITAE) are considered for optimization. The effectiveness of an objective function is considered based on the variation in tie line power and change in frequency in both the areas. MATLAB/SIMULINK was used as a simulation tool. Simulation results reveal that ITAE is a better objective function than ISE. Performances of optimization algorithms are also compared and it was found that genetic algorithm gives better results than particle swarm optimization algorithm for the problems of AGC.
Abstract: The model-based approach to user interface design
relies on developing separate models capturing various aspects about
users, tasks, application domain, presentation and dialog structures.
This paper presents a task modeling approach for user interface
design and aims at exploring mappings between task, domain and
presentation models. The basic idea of our approach is to identify
typical configurations in task and domain models and to investigate
how they relate each other. A special emphasis is put on applicationspecific
functions and mappings between domain objects and
operational task structures. In this respect, we will address two
layers in task decomposition: a functional (planning) layer and an
operational layer.
Abstract: This paper proposes a prototype of a lower-limb
rehabilitation system for recovering and strengthening patients-
injured lower limbs. The system is composed of traction motors for
each leg position, a treadmill as a walking base, tension sensors,
microcontrollers controlling motor functions and a main system with
graphic user interface. For derivation of reference or normal velocity
profiles of the body segment point, kinematic method is applied based
on the humanoid robot model using the reference joint angle data of
normal walking.
Abstract: In this paper, the discrete-time fuzzy BAM neural network with delays and impulses is studied. Sufficient conditions are obtained for the existence and global stability of a unique equilibrium of this class of fuzzy BAM neural networks with Lipschitzian activation functions without assuming their boundedness, monotonicity or differentiability and subjected to impulsive state displacements at fixed instants of time. Some numerical examples are given to demonstrate the effectiveness of the obtained results.
Abstract: A numerical method for Riccati equation is presented in this work. The method is based on the replacement of unknown functions through a truncated series of hybrid of block-pulse functions and Chebyshev polynomials. The operational matrices of derivative and product of hybrid functions are presented. These matrices together with the tau method are then utilized to transform the differential equation into a system of algebraic equations. Corresponding numerical examples are presented to demonstrate the accuracy of the proposed method.