Fuzzy Inference Research Papers - Academia.edu (original) (raw)
Fault diagnosis of industrial machineries become very much important for improving the quality of the manufacturing as well as for reducing the cost for product testing. In modern manufacturing scenario, a fast and reliable diagnosis... more
Fault diagnosis of industrial machineries become very much important for improving the quality of the manufacturing as well as for reducing the cost for product testing. In modern manufacturing scenario, a fast and reliable diagnosis system has turned into a challenging issue in the complex industrial environment. In this work, the diagnosis of gearbox is considered as a mean of health monitoring system by used lubricant. The proposed methodology has been performed on the basis of wear particle analysis in gearbox at offline stage. Possible wear characterization has been done by image vision system to interpret into soft computing techniques like fuzzy inference and neural network mechanisms. Basically, the maintenance policy has been taken with the help of fuzzy expert system, which has been described in the present work.
In this paper a k-nearest neighborhood based fuzzy reasoning is introduced. The proposed approach is necessary in order to estimate the firing degree of each rule for a fuzzy if-then rule base where the antecedent is an n-dimensional... more
In this paper a k-nearest neighborhood based fuzzy reasoning is introduced. The proposed approach is necessary in order to estimate the firing degree of each rule for a fuzzy if-then rule base where the antecedent is an n-dimensional vector. The proposed methodology is applied to well known Box and Jenkins gas-furnace data and compared with two other algorithms. The first
Credit institutions are seldom faced with problems dealing with single objectives. Often, decisions involving optimizing two or more competing goals simultaneously need to be made, and conventional optimization routines/models are... more
Credit institutions are seldom faced with problems dealing with single objectives. Often, decisions involving optimizing two or more competing goals simultaneously need to be made, and conventional optimization routines/models are incapable of handling the problems. This study applies the Fuzzy Simplex Generic Algorithm (a multi-objective optimization algorithm) in generating decision rules for predicting loan default in a typical credit institution. Empirical results show that the best indicators of default status are observed when repayment capacity and owners equity are low and the working capital is either low or high. Also, the two worst rule indicators are low repayment capacity, high owners’ equity and medium working capital or medium repayment capacity, low owners’ equity and high working capital.► We examine the difficulty of optimizing multiple goals in credit default forecast. ► This is problematic when competing decisions are being simultaneously optimized. ► Fuzzy Simplex Generic Algorithm is used to generate rules to predict loan defaults. ► The best indicator is low repayment capacity, owners’ equity, and working capital.
Efficient and effective response to the requirements of customers is a major performance indicator. Failure to satisfy customer requirements implies operational weaknesses in a company. These weaknesses will damage both the rights of... more
Efficient and effective response to the requirements of customers is a major performance indicator. Failure to satisfy customer requirements implies operational weaknesses in a company. These weaknesses will damage both the rights of customers and the reputation ...
We report on a fuzzy logic-based language understanding system applied to speech recognition. This system acquires conceptual knowledge from corpus data and organizes such knowledge into fuzzy logic inference rules. The system parses... more
We report on a fuzzy logic-based language understanding system applied to speech recognition. This system acquires conceptual knowledge from corpus data and organizes such knowledge into fuzzy logic inference rules. The system parses speech recognition results into conceptual structures in a robust manner, and thus is able to tolerate noise caused by speech recognition errors. We discuss the fuzzy inference rule learning method and explain its organization. Experimental results that demonstrate the ability of the system to deal with complex speech input instances are reported
The focus of this research is on the development, modeling and high precision robust control of an electro-mechanical continuum robot manipulator that serves as a sensing and motion system for hybrid testing. In this research parallel... more
The focus of this research is on the development, modeling and high precision robust control of an electro-mechanical continuum robot manipulator that serves as a sensing and motion system for hybrid testing. In this research parallel fuzzy logic theory is used to compensate the system dynamic uncertainty controller based on sliding mode theory. This design resulted in strongly non-linear and coupled dynamics as well as an inertial moving platform that attracted model-based control strategies. A novel non-linear control technique based on sliding mode Lyapunov based was selected to meet the multiple simultaneous specification control of nonlinear, uncertain and asymptotic tracking. Sliding mode controller (SMC) is a significant nonlinear controller under condition of partly uncertain dynamic parameters of system. This controller is used to control of highly nonlinear systems especially for continuum robot manipulator, because this controller is robust and stable in presence of partly uncertainties. Sliding mode controller was used to achieve a stable tracking, while the parallel fuzzy-logic optimization added intelligence to the control system through an automatic tuning of the sliding mode methodology uncertainties. Simulation results demonstrated the validity of the Mamdani parallel fuzzy-optimization control with asymptotic and stable tracking at different position inputs. This compensation demonstrated a well synchronized control signal at different excitation conditions.
A wire electrical discharge machined (WEDM) surface is characterized by its roughness and metallographic properties. Surface roughness and white layer thickness (WLT) are the main indicators of quality of a component for WEDM. In this... more
A wire electrical discharge machined (WEDM) surface is characterized by its roughness and metallographic properties. Surface roughness and white layer thickness (WLT) are the main indicators of quality of a component for WEDM. In this paper an adaptive neuro-fuzzy ...
In this paper, a PD-serial fuzzy based robust nonlinear estimator for a robot manipulator is proposed by using robust factorization approach. That is, considering the uncertainties of dynamic model consisting of measurement error and... more
In this paper, a PD-serial fuzzy based robust nonlinear estimator for a robot manipulator is proposed by using robust factorization approach. That is, considering the uncertainties of dynamic model consisting of measurement error and disturbances, a PD with fuzzy estimator variable structure nonlinear feedback control scheme is designed to reduce effect of uncertainties. This research aims to design a new methodology to fix the position in robot manipulator. PD method is a linear methodology which can be used for highly nonlinear system’s (e.g., robot manipulator). To estimate this method, new serial fuzzy variable structure method (PD.FVSM) is used. This estimator can estimate the parameters to have the best performance.
Refer to this paper, design lookup table changed adaptive fuzzy sliding mode controller with minimum rule base and good response in presence of structure and unstructured uncertainty is presented. However sliding mode controller is one... more
Refer to this paper, design lookup table changed adaptive fuzzy sliding mode controller with
minimum rule base and good response in presence of structure and unstructured uncertainty is
presented. However sliding mode controller is one of the robust nonlinear controllers but when
this controller is applied to robot manipulator with highly nonlinear and uncertain dynamic function;
caused to be challenged in control. Sliding mode controller in presence of uncertainty has two
most important drawbacks; chattering and nonlinear equivalent part which proposed method is
solved these challenges with look up table change methodology. This method is based on self
tuning methodology therefore artificial intelligence (e.g., fuzzy logic method) is played important
role to design proposed method. This controller has acceptable performance in presence of
uncertainty (e.g., overshoot=0%, rise time=0.8 s, steady state error = 1e-9 and RMS
error=0.00017).
This paper describes the hardware implementation of a PID-type (Proportional- Integral - Derivative) Fuzzy Logic Controller (FLC) algorithm using VHDL to use in transportation cruising system. The cruising system has developed to avoid... more
This paper describes the hardware implementation of a PID-type (Proportional- Integral - Derivative) Fuzzy Logic Controller (FLC) algorithm using VHDL to use in transportation cruising system. The cruising system has developed to avoid the collisions between vehicles on the road. The PID-type FLC provides a reference for a car to either increase or decrease the speed of the vehicle depending
In recent years, fuzzy-logic-based methods have demonstrated to be appropriated to address uncertainty and subjectivity in environmental problems. In the present study, a methodology based on fuzzy inference systems (FIS) to assess water... more
In recent years, fuzzy-logic-based methods have demonstrated to be appropriated to address uncertainty and subjectivity in environmental problems. In the present study, a methodology based on fuzzy inference systems (FIS) to assess water quality is proposed. A water quality index calculated with fuzzy reasoning has been developed. The relative importance of water quality indicators involved in the fuzzy inference process has been dealt with a multi-attribute decision-aiding method. The potential application of the fuzzy index has been tested with a case study. A data set collected from the Ebro River (Spain) by two different environmental protection agencies has been used. The current findings, managed within a geographic information system, clearly agree with official reports and expert opinions about the pollution problems in the studied area. Therefore, this methodology emerges as a suitable and alternative tool to be used in developing effective water management plans.
CHLFuzzy is a user-friendly, flexible, multiple-input single-output Takagi-Sugeno fuzzy rule based model developed in a MS-Excel® spreadsheet environment. The model receives a raw dataset consisting of four predictor variables, e.g.,... more
CHLFuzzy is a user-friendly, flexible, multiple-input single-output Takagi-Sugeno fuzzy rule based model developed in a MS-Excel® spreadsheet environment. The model receives a raw dataset consisting of four predictor variables, e.g., water temperature, dissolved oxygen content, dissolved inorganic nitrogen concentration, and solar radiation levels. It then defines fuzzy sets according to a collection of fuzzy membership functions, allowing for the establishment of fuzzy ‘if–then’ rules, and predicts chlorophyll-a concentrations, which highly compare to the measured ones. The performance of the model was tested against the Adaptive Neural Fuzzy Inference System (ANFIS), showing satisfactory results. An extensive dataset of environmental observations in Vassova Lagoon (Northern Greece), during the years 2001–2002, was used to train the model and an independent dataset collected during 2004 was used to validate CHLFuzzy and ANFIS models. Although both models showed a similar performance on the training dataset, with quite satisfactory agreement between observed and modeled chlorophyll-a values, the best results were obtained using the CHLfuzzy model. Similarly, the CHLfuzzy model depicted a fairly good ability to hindcast chlorophyll-a concentrations for the verification dataset, thus improving ANFIS model forecasts. Overall results suggest that CHLfuzzy can potentially be used as a lagoon water quality forecasting tool requiring limited computational cost.
Nowadays, the intelligent transportation concept has become one of the most important research fields. All of us depend on mobility, even when we talk about people, provide services, or move goods. Researchers have tried to create and... more
Nowadays, the intelligent transportation concept has become one of the most important research fields. All of us depend on mobility, even when we talk about people, provide services, or move goods. Researchers have tried to create and test different transportation models that can optimize traffic flow through road networks and, implicitly, reduce travel times. To validate these new models, the necessity of having a calibration process defined has emerged. Calibration is mandatory in the modeling process because it ensures the achievement of a model closer to the real system. The purpose of this paper is to propose a new multidisciplinary approach combining microscopic traffic modeling theory with intelligent control systems concepts like fuzzy inference in the traffic model calibration. The chosen Takagi-Sugeno fuzzy inference system proves its adaptive capacity for real-time systems. This concept will be applied to the specific microscopic car-following model parameters in combination with a Kalman filter. The results will demonstrate how the microscopic traffic model parameters can adapt based on real data to prove the model validity.
Abstract: - This paper describes the hardware implementation of a PID-type (Proportional-Integral - Derivative) Fuzzy Logic Controller (FLC) algorithm using VHDL to use in transportation cruising system. The cruising system has developed... more
Abstract: - This paper describes the hardware implementation of a PID-type (Proportional-Integral - Derivative) Fuzzy Logic Controller (FLC) algorithm using VHDL to use in transportation cruising system. The cruising system has developed to avoid the collisions between vehicles on ...