Abstract: In recent years the large scale use of the power electronic equipment has led to an increase of harmonics in the power system. The harmonics results into a poor power quality and have great adverse economical impact on the utilities and customers. Current harmonics are one of the most common power quality problems and are usually resolved by using shunt active filter (SHAF). The main objective of this work is to develop PI and Fuzzy logic controllers (FLC) to analyze the performance of Shunt Active Filter for mitigating current harmonics under balanced and unbalanced sinusoidal source voltage conditions for normal load and increased load. When the supply voltages are ideal (balanced), both PI and FLC are converging to the same compensation characteristics. However, the supply voltages are non-ideal (unbalanced), FLC offers outstanding results. Simulation results validate the superiority of FLC with triangular membership function over the PI controller.
Abstract: In this work Artificial Intelligence (AI) techniques like Fuzzy logic, Genetic Algorithms and Particle Swarm Optimization have been used to improve the performance of the Automatic Generation Control (AGC) system. Instead of applying Genetic Algorithms and Particle swarm optimization independently for optimizing the parameters of the conventional AGC with PI controller, an intelligent tuned Fuzzy logic controller (acting as the secondary controller in the AGC system) has been designed. The controller gives an improved dynamic performance for both hydrothermal and thermal-thermal power systems under a variety of operating conditions.
Abstract: Using of natural lighting has come into prominence in
constructed buildings, especially in last ten years, under scope of
energy efficiency. Natural lighting methods are one of the methods
that aim to take advantage of day light in maximum level and
decrease using of artificial lighting. Increasing of day light amount in
buildings by using suitable methods will give optimum result in
terms of comfort and energy saving when the daylight-artificial light
integration is ensured with a suitable control system. Using of natural
light in places that require lighting will ensure energy saving in great
extent. With this study, it is aimed to save energy used for purpose of
lighting. Under this scope, lighting of a scanning laboratory of a
hospital was realized by using a lighting automation containing
natural and artificial lighting. In natural lighting, light pipes were
used and in artificial lighting, dimmable power LED modules were
used. Necessity of lighting was followed with motion sensors. The
lighting automation containing natural and artificial light was ensured
with fuzzy logic control. At the scanning laboratory where this
application was realized, energy saving in lighting was obtained.
Abstract: A novel design of two-wheeled robotic vehicle with moving payload is presented in this paper. A mathematical model describing the vehicle dynamics is derived and simulated in Matlab Simulink environment. Two control strategies were developed to stabilise the vehicle in the upright position. A robust Proportional- Integral-Derivative (PID) control strategy has been implemented and initially tested to measure the system performance, while the second control strategy is to use a hybrid fuzzy logic controller (FLC). The results are given on a comparative basis for the system performance in terms of disturbance rejection, control algorithms robustness as well as the control effort in terms of input torque.
Abstract: Advancements in the field of artificial intelligence
(AI) made during this decade have forever changed the way we look
at automating spacecraft subsystems including the electrical power
system. AI have been used to solve complicated practical problems
in various areas and are becoming more and more popular nowadays.
In this paper, a mathematical modeling and MATLAB–SIMULINK
model for the different components of the spacecraft power system is
presented. Also, a control system, which includes either the Neural
Network Controller (NNC) or the Fuzzy Logic Controller (FLC) is
developed for achieving the coordination between the components of
spacecraft power system as well as control the energy flows. The
performance of the spacecraft power system is evaluated by
comparing two control systems using the NNC and the FLC.
Abstract: Vehicle which are turning or maneuvering at high speeds
are susceptible to sliding and subsequently deviate from desired path. In
this paper the dynamics governing the Yaw/Roll behavior of a vehicle
has been simulated. Two different simulations have been used one for
the real vehicle, for which a fuzzy controller is designed to increase its
directional stability property. The other simulation is for a hypothetical
vehicle with much higher tire cornering stiffness which is capable of
developing the required lateral forces at the tire-ground patch contact to
attain the desired lateral acceleration for the vehicle to follow the
desired path without slippage. This simulation model is our reference
model.
The logic for keeping the vehicle on the desired track in the cornering
or maneuvering state is to have some braking forces on the inner or
outer tires based on the direction of vehicle deviation from the desired
path. The inputs to our vehicle simulation model is steer angle δ and
vehicle velocity V , and the outputs can be any kinematical parameters
like yaw rate, yaw acceleration, side slip angle, rate of side slip angle
and so on. The proposed fuzzy controller is a feed forward controller.
This controller has two inputs which are steer angle δ and vehicle
velocity V, and the output of the controller is the correcting moment M,
which guides the vehicle back to the desired track. To develop the
membership functions for the controller inputs and output and the fuzzy
rules, the vehicle simulation has been run for 1000 times and the
correcting moment have been determined by trial and error. Results of
the vehicle simulation with fuzzy controller are very promising
and show the vehicle performance is enhanced greatly over the
vehicle without the controller. In fact the vehicle performance
with the controller is very near the performance of the reference
ideal model.
Abstract: In this study, a fuzzy-logic based control system was
designed to ensure that time and energy is saved during the operation
of load elevators which are used during the construction of tall
buildings. In the control system that was devised, for the load
elevators to work more efficiently, the energy interval where the
motor worked was taken as the output variable whereas the amount
of load and the building height were taken as input variables. The
most appropriate working intervals depending on the characteristics
of these variables were defined by the help of an expert. Fuzzy expert
system software was formed using Delphi programming language. In
this design, mamdani max-min inference mechanism was used and
the centroid method was employed in the clarification procedure. In
conclusion, it is observed that the system that was designed is
feasible and this is supported by statistical analyses..
Abstract: During the past decade, pond aeration systems have
been developed which will sustain large quantities of fish and
invertebrate biomass. Dissolved Oxygen (DO) is considered to be
among the most important water quality parameters in fish culture.
Fishponds in aquaculture farms are usually located in remote areas
where grid lines are at far distance. Aeration of ponds is required to
prevent mortality and to intensify production, especially when
feeding is practical, and in warm regions. To increase pond
production it is necessary to control dissolved oxygen. Artificial
intelligence (AI) techniques are becoming useful as alternate
approaches to conventional techniques or as components of
integrated systems. They have been used to solve complicated
practical problems in various areas and are becoming more and more
popular nowadays. This paper presents a new design of diffused
aeration system using fuel cell as a power source. Also fuzzy logic
control Technique (FLC) is used for controlling the speed of air flow
rate from the blower to air piping connected to the pond by adjusting
blower speed. MATLAB SIMULINK results show high performance
of fuzzy logic control (FLC).
Abstract: This paper attempts to model and design a simple
fuzzy logic controller with Variable Reference. The Variable
Reference (VR) is featured as an adaptability element which is
obtained from two known variables – desired system-input and actual
system-output. A simple fuzzy rule-based technique is simulated to
show how the actual system-input is gradually tuned in to a value
that closely matches the desired input. The designed controller is
implemented and verified on a simple heater which is controlled by
PIC Microcontroller harnessed by a code developed in embedded C.
The output response of the PIC-controlled heater is analyzed and
compared to the performances by conventional fuzzy logic
controllers. The novelty of this work lies in the fact that it gives
better performance by using less number of rules compared to
conventional fuzzy logic controllers.
Abstract: This paper presents a hybrid fuzzy-PD plus PID
(HFPP) controller and its application to steam distillation process for
essential oil extraction system. Steam temperature is one of the most
significant parameters that can influence the composition of essential
oil yield. Due to parameter variations and changes in operation
conditions during distillation, a robust steam temperature controller becomes nontrivial to avoid the degradation of essential oil quality.
Initially, the PRBS input is triggered to the system and output of steam temperature is modeled using ARX model structure. The
parameter estimation and tuning method is adopted by simulation
using HFPP controller scheme. The effectiveness and robustness of
proposed controller technique is validated by real time
implementation to the system. The performance of HFPP using 25 and 49 fuzzy rules is compared. The experimental result demonstrates the proposed HFPP using 49 fuzzy rules achieves a
better, consistent and robust controller compared to PID when considering the test on tracking the set point and the effects due to disturbance.
Abstract: This paper presents the use of anti-sway angle control
approaches for a two-dimensional gantry crane with disturbances
effect in the dynamic system. Delayed feedback signal (DFS) and
proportional-derivative (PD)-type fuzzy logic controller are the
techniques used in this investigation to actively control the sway
angle of the rope of gantry crane system. A nonlinear overhead
gantry crane system is considered and the dynamic model of the
system is derived using the Euler-Lagrange formulation. A complete
analysis of simulation results for each technique is presented in time
domain and frequency domain respectively. Performances of both
controllers are examined in terms of sway angle suppression and
disturbances cancellation. Finally, a comparative assessment of the
impact of each controller on the system performance is presented and
discussed.
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 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.