Abstract: In this research paper we have presented control
architecture for robotic arm movement and trajectory planning using
Fuzzy Logic (FL) and Genetic Algorithms (GAs). This architecture is
used to compensate the uncertainties like; movement, friction and
settling time in robotic arm movement. The genetic algorithms and
fuzzy logic is used to meet the objective of optimal control
movement of robotic arm. This proposed technique represents a
general model for redundant structures and may extend to other
structures. Results show optimal angular movement of joints as result
of evolutionary process. This technique has edge over the other
techniques as minimum mathematics complexity used.
Abstract: Fuzzy logic control (FLC) systems have been tested in
many technical and industrial applications as a useful modeling tool
that can handle the uncertainties and nonlinearities of modern control
systems. The main drawback of the FLC methodologies in the
industrial environment is challenging for selecting the number of
optimum tuning parameters.
In this paper, a method has been proposed for finding the optimum
membership functions of a fuzzy system using particle swarm
optimization (PSO) algorithm. A synthetic algorithm combined from
fuzzy logic control and PSO algorithm is used to design a controller
for a continuous stirred tank reactor (CSTR) with the aim of
achieving the accurate and acceptable desired results. To exhibit the
effectiveness of proposed algorithm, it is used to optimize the
Gaussian membership functions of the fuzzy model of a nonlinear
CSTR system as a case study. It is clearly proved that the optimized
membership functions (MFs) provided better performance than a
fuzzy model for the same system, when the MFs were heuristically
defined.
Abstract: This paper investigates and compares performance of
various conventional and fuzzy logic based controllers at generator
locations for oscillation damping. Performance of combination of
conventional and fuzzy logic based controllers also studied by
comparing overshoot on the active power deviation response for a
small disturbance and damping ratio of the critical mode. Fuzzy logic
based controllers can not be modeled in the state space form to get
the eigenvalues and corresponding damping ratios of various modes
of generators and controllers. Hence, a new method based on tracing
envelop of time domain waveform is also presented and used in the
paper for comparing performance of controllers. The paper also
shows that if the fuzzy based controllers designed separately
combining them could not lead to a better performance.
Abstract: The production of a plant can be measured in terms of
seeds. The generation of seeds plays a critical role in our social and
daily life. The fruit production which generates seeds, depends on the
various parameters of the plant, such as shoot length, leaf number,
root length, root number, etc When the plant is growing, some leaves
may be lost and some new leaves may appear. It is very difficult to
use the number of leaves of the tree to calculate the growth of the
plant.. It is also cumbersome to measure the number of roots and
length of growth of root in several time instances continuously after
certain initial period of time, because roots grow deeper and deeper
under ground in course of time. On the contrary, the shoot length of
the tree grows in course of time which can be measured in different
time instances. So the growth of the plant can be measured using the
data of shoot length which are measured at different time instances
after plantation. The environmental parameters like temperature, rain
fall, humidity and pollution are also play some role in production of
yield. The soil, crop and distance management are taken care to
produce maximum amount of yields of plant. The data of the growth
of shoot length of some mustard plant at the initial stage (7,14,21 &
28 days after plantation) is available from the statistical survey by a
group of scientists under the supervision of Prof. Dilip De. In this
paper, initial shoot length of Ken( one type of mustard plant) has
been used as an initial data. The statistical models, the methods of
fuzzy logic and neural network have been tested on this mustard
plant and based on error analysis (calculation of average error) that
model with minimum error has been selected and can be used for the
assessment of shoot length at maturity. Finally, all these methods
have been tested with other type of mustard plants and the particular
soft computing model with the minimum error of all types has been
selected for calculating the predicted data of growth of shoot length.
The shoot length at the stage of maturity of all types of mustard
plants has been calculated using the statistical method on the
predicted data of shoot length.
Abstract: Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE workand output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-by-stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.
Abstract: The present paper proposes high performance nonlinear
force controllers for a servopneumatic real-time fatigue test
machine. A CompactRIO® controller was used, being fully
programmed using LabVIEW language. Fuzzy logic control
algorithms were evaluated to tune the integral and derivative
components in the development of hybrid controllers, namely a FLC
P and a hybrid FLC PID real-time-based controllers. Their
behaviours were described by using state diagrams. The main
contribution is to ensure a smooth transition between control states,
avoiding discrete transitions in controller outputs. Steady-state errors
lower than 1.5 N were reached, without retuning the controllers.
Good results were also obtained for sinusoidal tracking tasks from
1/¤Ç to 8/¤Ç Hz.
Abstract: Actual load, material characteristics and other
quantities often differ from the design values. This can cause worse
function, shorter life or failure of a civil engineering structure, a
machine, vehicle or another appliance. The paper shows main causes
of the uncertainties and deviations and presents a systematic
approach and efficient tools for their elimination or mitigation of
consequences. Emphasis is put on the design stage, which is most
important for reliability ensuring. Principles of robust design and
important tools are explained, including FMEA, sensitivity analysis
and probabilistic simulation methods. The lifetime prediction of
long-life objects can be improved by long-term monitoring of the
load response and damage accumulation in operation. The condition
evaluation of engineering structures, such as bridges, is often based
on visual inspection and verbal description. Here, methods based on
fuzzy logic can reduce the subjective influences.
Abstract: The existence of maximal durations drastically modifies the performance evaluation in Discrete Event Systems (DES). The same particularity may be found on systems where the associated constraints do not concern the time. For example weight measures, in chemical industry, are used in order to control the quantity of consumed raw materials. This parameter also takes a fundamental part in the product quality as the correct transformation process is based upon a given percentage of each essence. Weight regulation therefore increases the global productivity of the system by decreasing the quantity of rejected products. In this paper we present an approach based on mixing different characteristics theories, the fuzzy system and Petri net system to describe the behaviour. An industriel application on a tobacco manufacturing plant, where the critical parameter is the weight is presented as an illustration.