Abstract: A direct adaptive controller for a class of unknown nonlinear discrete-time systems is presented in this article. The proposed controller is constructed by fuzzy rules emulated network (FREN). With its simple structure, the human knowledge about the plant is transferred to be if-then rules for setting the network. These adjustable parameters inside FREN are tuned by the learning mechanism with time varying step size or learning rate. The variation of learning rate is introduced by main theorem to improve the system performance and stabilization. Furthermore, the boundary of adjustable parameters is guaranteed through the on-line learning and membership functions properties. The validation of the theoretical findings is represented by some illustrated examples.
Abstract: In this paper we have numerically analyzed terahertzrange
wavelength conversion using nondegenerate four wave mixing
(NDFWM) in a SOA integrated DFB laser (experiments reported
both in MIT electronics and Fujitsu research laboratories). For
analyzing semiconductor optical amplifier (SOA), we use finitedifference
beam propagation method (FDBPM) based on modified
nonlinear SchrÖdinger equation and for distributed feedback (DFB)
laser we use coupled wave approach. We investigated wavelength
conversion up to 4THz probe-pump detuning with conversion
efficiency -5dB in 1THz probe-pump detuning for a SOA integrated
quantum-well
Abstract: This paper presents a longitudinal quasi-linear model for the ADMIRE model. The ADMIRE model is a nonlinear model of aircraft flying in the condition of high angle of attack. So it can-t be considered to be a linear system approximately. In this paper, for getting the longitudinal quasi-linear model of the ADMIRE, a state transformation based on differentiable functions of the nonscheduling states and control inputs is performed, with the goal of removing any nonlinear terms not dependent on the scheduling parameter. Since it needn-t linear approximation and can obtain the exact transformations of the nonlinear states, the above-mentioned approach is thought to be appropriate to establish the mathematical model of ADMIRE. To verify this conclusion, simulation experiments are done. And the result shows that this quasi-linear model is accurate enough.
Abstract: This paper deals with a high-order accurate Runge
Kutta Discontinuous Galerkin (RKDG) method for the numerical
solution of the wave equation, which is one of the simple case of a
linear hyperbolic partial differential equation. Nodal DG method is
used for a finite element space discretization in 'x' by discontinuous
approximations. This method combines mainly two key ideas which
are based on the finite volume and finite element methods. The
physics of wave propagation being accounted for by means of
Riemann problems and accuracy is obtained by means of high-order
polynomial approximations within the elements. High order accurate
Low Storage Explicit Runge Kutta (LSERK) method is used for
temporal discretization in 't' that allows the method to be nonlinearly
stable regardless of its accuracy. The resulting RKDG
methods are stable and high-order accurate. The L1 ,L2 and L∞ error
norm analysis shows that the scheme is highly accurate and effective.
Hence, the method is well suited to achieve high order accurate
solution for the scalar wave equation and other hyperbolic equations.
Abstract: The quality of short term load forecasting can improve the efficiency of planning and operation of electric utilities. Artificial Neural Networks (ANNs) are employed for nonlinear short term load forecasting owing to their powerful nonlinear mapping capabilities. At present, there is no systematic methodology for optimal design and training of an artificial neural network. One has often to resort to the trial and error approach. This paper describes the process of developing three layer feed-forward large neural networks for short-term load forecasting and then presents a heuristic search algorithm for performing an important task of this process, i.e. optimal networks structure design. Particle Swarm Optimization (PSO) is used to develop the optimum large neural network structure and connecting weights for one-day ahead electric load forecasting problem. PSO is a novel random optimization method based on swarm intelligence, which has more powerful ability of global optimization. Employing PSO algorithms on the design and training of ANNs allows the ANN architecture and parameters to be easily optimized. The proposed method is applied to STLF of the local utility. Data are clustered due to the differences in their characteristics. Special days are extracted from the normal training sets and handled separately. In this way, a solution is provided for all load types, including working days and weekends and special days. The experimental results show that the proposed method optimized by PSO can quicken the learning speed of the network and improve the forecasting precision compared with the conventional Back Propagation (BP) method. Moreover, it is not only simple to calculate, but also practical and effective. Also, it provides a greater degree of accuracy in many cases and gives lower percent errors all the time for STLF problem compared to BP method. Thus, it can be applied to automatically design an optimal load forecaster based on historical data.
Abstract: In this paper we propose and examine an Adaptive
Neuro-Fuzzy Inference System (ANFIS) in Smoothing Transition
Autoregressive (STAR) modeling. Because STAR models follow
fuzzy logic approach, in the non-linear part fuzzy rules can be
incorporated or other training or computational methods can be
applied as the error backpropagation algorithm instead to nonlinear
squares. Furthermore, additional fuzzy membership functions can be
examined, beside the logistic and exponential, like the triangle,
Gaussian and Generalized Bell functions among others. We examine
two macroeconomic variables of US economy, the inflation rate and
the 6-monthly treasury bills interest rates.
Abstract: This paper presents three-phase evolution search methodology to automatically design fuzzy logic controllers (FLCs) that can work in a wide range of operating conditions. These include varying load, parameter variations, and unknown external disturbances. The three-phase scheme consists of an exploration phase, an exploitation phase and a robustness phase. The first two phases search for FLC with high accuracy performances while the last phase aims at obtaining FLC providing the best compromise between the accuracy and robustness performances. Simulations were performed for direct-drive two-axis robot arm. The evolved FLC with the proposed design technique found to provide a very satisfactory performance under the wide range of operation conditions and to overcome problem associated with coupling and nonlinearities characteristics inherent to robot arms.
Abstract: In this paper a comprehensive model of a fossil fueled
power plant (FFPP) is developed in order to evaluate the
performance of a newly designed turbine follower controller.
Considering the drawbacks of previous works, an overall model is
developed to minimize the error between each subsystem model
output and the experimental data obtained at the actual power plant.
The developed model is organized in two main subsystems namely;
Boiler and Turbine. Considering each FFPP subsystem
characteristics, different modeling approaches are developed. For
economizer, evaporator, superheater and reheater, first order models
are determined based on principles of mass and energy conservation.
Simulations verify the accuracy of the developed models. Due to the
nonlinear characteristics of attemperator, a new model, based on a
genetic-fuzzy systems utilizing Pittsburgh approach is developed
showing a promising performance vis-à-vis those derived with other
methods like ANFIS. The optimization constraints are handled
utilizing penalty functions. The effect of increasing the number of
rules and membership functions on the performance of the proposed
model is also studied and evaluated. The turbine model is developed
based on the equation of adiabatic expansion. Parameters of all
evaluated models are tuned by means of evolutionary algorithms.
Based on the developed model a fuzzy PI controller is developed. It
is then successfully implemented in the turbine follower control
strategy of the plant. In this control strategy instead of keeping
control parameters constant, they are adjusted on-line with regard to
the error and the error rate. It is shown that the response of the
system improves significantly. It is also shown that fuel consumption
decreases considerably.
Abstract: The complex shape of the human pelvic bone was
successfully imaged and modeled using finite element FE processing.
The bone was subjected to quasi-static and dynamic loading
conditions simulating the effect of both weight gain and impact.
Loads varying between 500 – 2500 N (~50 – 250 Kg of weight) was
used to simulate 3D quasi-static weight gain. Two different 3D
dynamic analyses, body free fall at two different heights (1 and 2 m)
and forced side impact at two different velocities (20 and 40 Km/hr)
were also studied. The computed resulted stresses were compared for
the four loading cases, where Von Misses stresses increases linearly
with the weight gain increase under quasi-static loading. For the
dynamic models, the Von Misses stress history behaviors were
studied for the affected area and effected load with respect to time.
The normalization Von Misses stresses with respect to the applied
load were used for comparing the free fall and the forced impact load
results. It was found that under the forced impact loading condition
an over lapping behavior was noticed, where as for the free fall the
normalized Von Misses stresses behavior was found to nonlinearly
different. This phenomenon was explained through the energy
dissipation concept. This study will help designers in different
specialization in defining the weakest spots for designing different
supporting systems.
Abstract: Nonlinear and unbalance loads in three phase
networks create harmonics and losses. Active and passive filters are
used for elimination or reduction of these effects. Passive filters have
some limitations. For example, they are designed only for a specific
frequency and they may cause to resonance in the network at the
point of common coupling. The other drawback of a passive filter is
that the sizes of required elements are normally large. The active
filter can improve some of limitations of passive filter for example;
they can eliminate more than one harmonic and don't cause resonance
in the network. In this paper inverter analysis have been done
simultaneously in three phase and the RL impedance of the line have
been considered. A sliding mode control based on energy feedback of
capacitors is employed in the design with this method, the dynamic
speed of the filter is improved effectively and harmonics and load
unbalance is compensating quickly.
Abstract: Lateral-torsional buckling (LTB) is one of the
phenomenae controlling the ultimate bending strength of steel Ibeams
carrying distributed loads on top flange. Built-up I-sections
are used as main beams and distributors. This study investigates the
ultimate bending strength of such beams with sections of different
classes including slender elements. The nominal strengths of the
selected beams are calculated for different unsupported lengths
according to the Provisions of the American Institute of Steel
Constructions (AISC-LRFD). These calculations are compared with
results of a nonlinear inelastic study using accurate FE model for this
type of loading. The goal is to investigate the performance of the
provisions for the selected sections. Continuous distributed load at
the top flange of the beams was applied at the FE model.
Imperfections of different values are implemented to the FE model to
examine their effect on the LTB of beams at failure, and hence, their
effect on the ultimate strength of beams. The study also introduces a
procedure for evaluating the performance of the provisions compared
with the accurate FEA results of the selected sections. A simplified
design procedure is given and recommendations for future code
updates are made.
Abstract: In this paper, application of Sliding Mode Control (SMC) technique for an Active Magnetic Bearing (AMB) system with varying rotor speed is considered. The gyroscopic effect and mass imbalance inherited in the system is proportional to rotor speed in which this nonlinearity effect causes high system instability as the rotor speed increases. Transformation of the AMB dynamic model into regular system shows that these gyroscopic effect and imbalance lie in the mismatched part of the system. A H2-based sliding surface is designed which bound the mismatched parts. The solution of the surface parameter is obtained using Linear Matrix Inequality (LMI). The performance of the controller applied to the AMB model is demonstrated through simulation works under various system conditions.
Abstract: Method of multiple scales is used in the paper in order
to derive an amplitude evolution equation for the most unstable mode
from two-dimensional shallow water equations under the rigid-lid
assumption. It is assumed that shallow mixing layer is slightly curved
in the longitudinal direction and contains small particles. Dynamic
interaction between carrier fluid and particles is neglected. It is
shown that the evolution equation is the complex Ginzburg-Landau
equation. Explicit formulas for the computation of the coefficients of
the equation are obtained.
Abstract: In This paper, the behavior of eccentric braced frame
(EBF) is studied with replacing friction damper (FD) in confluence of these braces, in 5 and 10-storey steel frames. For FD system, the main step is to determine the slip load. For this reason, the performance indexes include roof displacement, base shear, dissipated energy and relative performance should be investigated. In
nonlinear dynamic analysis, the response of structure to three
earthquake records has been obtained and the values of roof
displacement, base shear and column axial force for FD and EBF
frames have been compared. The results demonstrate that use of the FD in frames, in comparison with the EBF, substantially reduces the roof displacement, column axial force and base shear. The obtained results show suitable performance of FD in higher storey structure in
comparison with the EBF.
Abstract: A nonlinear model of two-beam free-electron laser
(FEL) in the absence of slippage is presented. The two beams are
assumed to be cold with different energies and the fundamental
resonance of the higher energy beam is at the third harmonic of lower
energy beam. By using Maxwell-s equations and full Lorentz force
equations of motion for the electron beams, coupled differential
equations are derived and solved numerically by the fourth order
Runge–Kutta method. In this method a considerable growth of third
harmonic electromagnetic field in the XUV and X-ray regions is
predicted.
Abstract: The very nonlinear nature of the generator and system
behaviour following a severe disturbance precludes the use of
classical linear control technique. In this paper, a new approach of
nonlinear control is proposed for transient and steady state stability
analysis of a synchronous generator. The control law of the generator
excitation is derived from the basis of Lyapunov stability criterion.
The overall stability of the system is shown using Lyapunov
technique. The application of the proposed controller to simulated
generator excitation control under a large sudden fault and wide
range of operating conditions demonstrates that the new control
strategy is superior to conventional automatic voltage regulator
(AVR), and show very promising results.
Abstract: In this paper we consider a nonlinear feedback
control called augmented automatic choosing control (AACC)
using the automatic choosing functions of gradient optimization
type 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 minimizing the Hamiltonian
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: The objective of this paper is to present a
comparative study of Homotopy Perturbation Method (HPM),
Variational Iteration Method (VIM) and Homotopy Analysis
Method (HAM) for the semi analytical solution of Kortweg-de
Vries (KdV) type equation called KdV. The study have been
highlighted the efficiency and capability of aforementioned methods
in solving these nonlinear problems which has been arisen from a
number of important physical phenomenon.
Abstract: We propose a new approach on how to obtain the approximate solutions of Hamilton-Jacobi (HJ) equations. The process of the approximation consists of two steps. The first step is to transform the HJ equations into the virtual time based HJ equations (VT-HJ) by introducing a new idea of ‘virtual-time’. The second step is to construct the approximate solutions of the HJ equations through a computationally iterative procedure based on the VT-HJ equations. It should be noted that the approximate feedback solutions evolve by themselves as the virtual-time goes by. Finally, we demonstrate the effectiveness of our approximation approach by means of simulations with linear and nonlinear control problems.
Abstract: The problem of lot sizing, sequencing and scheduling
multiple products in flow line production systems has been studied
by several authors. Almost all of the researches in this area assumed
that setup times and costs are sequence –independent even though
sequence dependent setups are common in practice. In this paper we
present a new mixed integer non linear program (MINLP) and a
heuristic method to solve the problem in sequence dependent case.
Furthermore, a genetic algorithm has been developed which applies
this constructive heuristic to generate initial population. These two
proposed solution methods are compared on randomly generated
problems. Computational results show a clear superiority of our
proposed GA for majority of the test problems.