8,577 research outputs found
Sistema fuzzy tipo-2 intervalar implementado em FPGA baseado no algoritmo de Nie-Tan
This work aims to propose and validate an architecture of an interval type-2 fuzzy logic systems implemented in FPGA, which meets real-time control applications, with serial processing in the inference mechanisms. This work presents the design and implementation of the circuits that make up the interval type-2 fuzzy logic systems, such as: the type-2 interval fuzzifier circuit (FOU); the minimum and maximum circuits that are used in the Mamdani inference mechanism (type-2); the circuit applied to the state machine that is used by the rules base and the circuit that processes the reducer-type and defuzzification operations based on the Nie-Tan algorithm. The hardware presented has two 8-bit inputs with four Gaussian pertinence functions for each input, sixteen rules, and an 8-bit output with seven pertinence functions. Finally, the results of the FPGA implementation are validated using the same interval type-2 fuzzy logic systems implemented in Matlab® with a Toolbox for type-2 fuzzyAgência 1O presente trabalho tem como objetivo propor e validar uma arquitetura de um Sistema de Inferência Fuzzy (SIF) tipo-2 intervalar implementado em FPGA, que atenda aplicações de controle em tempo real, com processamento série no mecanismos de inferência. Neste trabalho são apresentados o projeto e a implementação dos circuitos que compõem o SIF tipo-2 intervalar, tais como: o circuito fuzificador tipo-2 intervalar (FOU); os circuitos de mínimo e máximo que são utilizados no mecanismo de inferência Mamdani (tipo-2); o circuito aplicado a máquina de estados que é utilizada pela base de regras e o circuito que processa as operações de tipo-redutor e defuzificação baseado no algoritmo de Nie-Tan. O hardware apresentado possui duas entradas de 8 bits com quatro funções de pertinência gaussianas para cada entrada, dezesseis regras e uma saída de 8 bits com sete funções de pertinência. E por fim, os resultados da implementação em FPGA são validados utilizando o mesmo SIF tipo-2 intervalar implementado no Matlab® com a Toolbox para type-2 fuzzy
Peramalan beban jangka pendek untuk hari libur nasional menggunakan interval type-2 fuzzy inference system (studi kasus : sistem kelistrikan Jawa-Bali)
Kebutuhan energi listrik sangat dipengaruhi oleh perilaku beban yang
tidak menentu. Di sisi lain, penyedia energi listrik dituntut harus mampu
menjamin kontinuitas kebutuhan beban untuk saat ini dan meramalkan kebutuhan
beban untuk masa yang akan datang. Perbedaan hari libur dan hari biasa
mengakibatkan karakteristrik beban listrik menjadi sangat kompleks dan
nonliniear, Oleh karena itu masalah peramalaan beban jangka pendek sangat perlu
didukung oleh metode komputasi untuk simulasi dan validasi.
Fuzzy logic adalah metode yang handal untuk peramalan beban pada
sistem yang kompleks dan non-liniear karena dapat mengubah variabel sistem ke
bentuk linguistik dalam reasoning approximation. Interval type-2 fuzzy inference
system (IT2FIS) merupakan pengembangan metode Interval type-1 fuzzy inference
system (IT1FIS) yang sangat tepat untuk digunakan pada peramalan beban karena
mempunyai kelebihan yang sangat fleksibel dalam perubahan footprint of
uncertainty (FOU), sehingga sangat mendukung untuk membentuk pemrosesan
awal data time series, komputasi, simulasi dan validasi model sistem.
Pada penelitian ini dilakukan simulai peramalan beban jangka pendek
menggunakan Interval type-2 fuzzy logic toolbox (IT2FLT). Performansi error
hasil prediksi yang diperoleh dari perbandingan nilai peramalan dengan nilai-nilai
aktualnya ditunjukkan oleh nilai mean absolute percentage error (MAPE).
Akurasi yang didapat dari hasil forecasting beban jangka pendek dengan metode
permodelan fuzzy type -2 dihasilkan error secara umum lebih kecil dibandingkan
dengan metode type-1. Metode peramalan tersebut memiliki MAPE terendah pada tahun 2010 yaitu sebesar 1,2658% sedangkan MAPE tertinggi terjadi pada tahun
2011yaitu sebesar 5,782%.
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The electrical energy requirement is strongly influenced by uncertain behavior of
the load. On the other side, the electric energy provider is required to be able to ensure
continuity of load demand at this time, and forecast for the future. The difference of
holidays and ordinary days resulted characteristics of the electrical load becomes very
complex and nonlinear, therefore the problem of short-term load forecasting very need to
be supported by computational methods for simulation and validation.
Fuzzy logic is a reliable method for forecasting the load on the system that
complex and non-linear because it can change system variables into linguistic form
through reasoning approximation. Interval type-2 fuzzy inference system (IT2FIS) as the
development of methods of Interval type-1 fuzzy inference system (IT1FIS), it is
appropriate to be used in load forecasting because it has the advantages that very flexible
on the change of the footprint of uncertainty (FOU), so it supports to establish initial
processing of the data time series , computing, simulation and validation of system
models.
In this research carried out simulations of short-term load forecasting using
Interval type-2 fuzzy logic toolbox (IT2FLT). The error performance of the prediction
result obtained from the comparison of the value of forecasting against actual values
indicated by the mean absolute percentage error (MAPE). The accuracy of the results
obtained from short-term load forecasting using fuzzy type-2 method, generally resulting
error is smaller than the type-1 method. The forecasting method has the lowest MAPE in
2010 in the amount of 1.2658% while the highest MAPE occurred in 2011 in the amount
of 5.782%
Fuzzy investment decision support for brownfield redevelopment
Tato disertační práce se zaměřuje na problematiku investování a podporu rozhodování pomocí moderních metod. Zejména pokud jde o analýzu, hodnocení a výběr tzv. brownfieldů pro jejich redevelopment (revitalizaci). Cílem této práce je navrhnout univerzální metodu, která usnadní rozhodovací proces. Proces rozhodování je v praxi komplikován též velkým počet relevantních parametrů ovlivňujících konečné rozhodnutí. Navržená metoda je založena na využití fuzzy logiky, modelování, statistické analýzy, shlukové analýzy, teorie grafů a na sofistikovaných metodách sběru a zpracování informací. Nová metoda umožňuje zefektivnit proces analýzy a porovnávání alternativních investic a přesněji zpracovat velký objem informací. Ve výsledku tak bude zmenšen počet prvků množiny nejvhodnějších alternativních investic na základě hierarchie parametrů stanovených investorem.This dissertation focuses on decision making, investing and brownfield redevelopment. Especially on the analysis, evaluation and selection of previously used real estates suitable for commercial use. The objective of this dissertation is to design a method that facilitates the decision making process with many possible alternatives and large number of relevant parameters influencing the decision. The proposed method is based on the use of fuzzy logic, modeling, statistic analysis, cluster analysis, graph theory and sophisticated methods of information collection and processing. New method allows decision makers to process much larger amount of information and evaluate possible investment alternatives efficiently.
Intelligent active force control of a three-link manipulator using fuzzy logic
The paper presents a novel approach to estimate the inertia matrix of a robot arm using a fuzzy logic (FL) mechanism in order to trigger the active force control (AFC) strategy. A comprehensive study is performed on a rigid three-link manipulator subjected to a number of external disturbances. The robustness and effectiveness of the proposed control scheme are investigated considering the trajectory track performance of the robotic arm taking into account the application of external disturbances and that the arm is commanded to describe a reference trajectory given a number of initial and operating conditions. The results show that the FL mechanism used in the study successfully computes appropriate estimated inertia matrix value to execute the control action. The proposed scheme exhibits a high degree of robustness and accuracy as the track error is bounded within an acceptable range of value even under the influence of the introduced disturbances
Grid Power Quality Enhancement Using Fuzzy Control-Based Shunt Active Filtering
Active filtering has proved efficient for the mitigation of harmonics in distribution grids. This paper deals with the design of fuzzy control strategies for a three-phase shunt active filter to enhance the power quality via the regulation of the DC bus voltage of the distribution network. The proposed control scheme is based on Interval Type 2 Fuzzy Logic controller. A simulation study is performed under Simulink/Matlab to evaluate the performance and robustness of the proposed control schemePeer reviewedFinal Accepted Versio
Analysis and Application of Advanced Control Strategies to a Heating Element Nonlinear Model
open4siSustainable control has begun to stimulate research and development in a wide range of industrial communities particularly for systems that demand a high degree of reliability and availability (sustainability) and at the same time characterised by expensive and/or safety critical maintenance work.
For heating systems such as HVAC plants, clear conflict exists between ensuring a high degree of availability and reducing costly maintenance times.
HVAC systems have highly non-linear dynamics and a stochastic and uncontrollable driving force as input in the form of intake air speed, presenting an interesting challenge for modern control methods. Suitable control methods can provide sustainable maximisation of energy conversion efficiency over wider than normally expected air speeds and temperatures, whilst also giving a degree of “tolerance” to certain faults, providing an important impact on maintenance scheduling, e.g. by capturing the effects of some system faults before they become serious.This paper presents the design of different control strategies applied to a heating element nonlinear model. The description of this heating element was obtained exploiting a data driven and physically meaningful nonlinear continuous time model, which represents a test bed used in passive air conditioning for sustainable housing applications. This model has low complexity while achieving high simulation performance. The physical meaningfulness of the model provides an enhanced insight into the performance and functionality of the system. In return, this information can be used during the system simulation and improved model based and data driven control designs for tight temperature regulation. The main purpose of this study is thus to give several examples of viable and practical designs of control schemes with application to this heating element model. Moreover, extensive simulations and Monte Carlo analysis are the tools for assessing experimentally the main features of the proposed control schemes, in the presence of modelling and measurement errors. These developed control methods are also compared in order to evaluate advantages and drawbacks of the considered solutions. Finally, the exploited simulation tools can serve to highlight the potential application of the proposed control strategies to real air conditioning systems.openTurhan, T.; Simani, S.; Zajic, I.; Gokcen Akkurt, G.Turhan, T.; Simani, Silvio; Zajic, I.; Gokcen Akkurt, G
Power-Constrained Fuzzy Logic Control of Video Streaming over a Wireless Interconnect
Wireless communication of video, with Bluetooth as an example, represents a compromise between channel conditions, display and decode deadlines, and energy constraints. This paper proposes fuzzy logic control (FLC) of automatic repeat request (ARQ) as a way of reconciling these factors, with a 40% saving in power in the worst channel conditions from economizing on transmissions when channel errors occur. Whatever the channel conditions are, FLC is shown to outperform the default Bluetooth scheme and an alternative Bluetooth-adaptive ARQ scheme in terms of reduced packet loss and delay, as well as improved video quality
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