Search results for "fuzzy"
showing 10 items of 747 documents
Using adaptive fuzzy-neural control to minimize response time in cluster-based web systems
2005
We have developed content-aware request distribution algorithm called FARD which is a client-and-server-aware, dynamic and adaptive distribution policy in cluster-based Web systems. It assigns each incoming request to the server with the least expected response time. To estimate the expected response times it uses the fuzzy estimation mechanism. The system is adaptive as it uses a neural network learning ability for its adaptation. Simulations based on traces from the 1998 World Cup show that when we consider the response time, FARD can be more effective than the state-of-the-art content-aware policy LARD.
Predicting the Short-Term Exchange Rate Between United State Dollar and Czech Koruna Using Hilbert-Huang Transform and Fuzzy Logic
2017
In this paper, the combination of the Hilbert-Huang Transform, fuzzy logic and an embedding theorem is described to predict the short-term exchange rate from United States dollar to Czech Koruna. By Using the Hilbert-Huang Transform as an adaptive filter, the proposed method decreases the embedding dimension space from five (original samples) to four (de-noising samples). This dimension space provides the number of inputs to the fuzzy rule base system, which causes the number of rules, the time for training and the inference process to decrease. Experimental results indicated that this method achieves higher accuracy prediction than the direct use of original data.
Fuzzy control of pH using NAL
1991
Abstract A fuzzy controller for a neutralization process is described. The controller was set up for a laboratory pilot plant. The approach is shown to be effective and can be extended to highly nonlinear and nonstationary processes. The “operator” knowledge encoded in the rules was obtained by several experimental runs of the system using manual control. Rules are composed using the max-min compositional rule of inference. The use of metarules, which depends on controller performance and on active disturbances, makes the controller behave like an adaptive controller. The control program is encoded in NAL, a new experimental logic programming language that was first used in this work in a r…
Fuzzy modeling and control for a class of inverted pendulum system
2014
Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/936868 Open Access Focusing on the issue of nonlinear stability control system about the single-stage inverted pendulum, the T-S fuzzy model is employed. Firstly, linear approximation method would be applied into fuzzy model for the single-stage inverted pendulum. At the same time, for some nonlinear terms which could not be dealt with via linear approximation method, this paper will adopt fan range method into fuzzy model. After the T-S fuzzy model, the PDC technology is utilized to design the fuzzy controller secondly. Numerical simulation res…
Prediction of stock index futures prices based on fuzzy sets and multivariate fuzzy time series
2015
Abstract This paper makes a prediction of Chinese stock index (CSI) future prices using fuzzy sets and multivariate fuzzy time series method. We select Chinese CSI 300 index futures as the research object. The fuzzy time series model combines the fuzzy theory and the time series theory, thus this model can solve the fuzzy data in stock index futures prices. This paper establishes a multivariate model and improves the accuracy of computation. By combing traditional fuzzy time series models and rough set method, we use fuzzy c-mean algorithm to make the data into discrete. Further more, we deal with the rules in mature modules of the rough set and then refine the rules using data mining algor…
Improved Performance of a PV Solar Panel with Adaptive Neuro Fuzzy Inference System ANFIS based MPPT
2018
This article presents the development of an intelligent technique of Adaptive-Neuro-Fuzzy Inference System (ANFIS) based on Maximum Power Point Tracking (ANFIS-MPPT) algorithm with PI controller in order to increase the performances of the photovoltaic panel system below change atmospheric circumstances. In this work, the mathematical principles of the ANFIS method were presented and developed using the software Matlab/Simulink. Moreover, the effectiveness of this ANFIS-MPPT technique is demonstrated by a comparison of the obtained results with others obtained from a classical (Perturb & Observe) P & O-MPPT method.From the analysis of the obtained results, the ANFIS-MPPT command provide bet…
Data-based modeling of vehicle crash using adaptive neural-fuzzy inference system
2014
Vehicle crashes are considered to be events that are extremely complex to be analyzed from the mathematical point of view. In order to establish a mathematical model of a vehicle crash, one needs to consider various areas of research. For this reason, to simplify the analysis and improve the modeling process, in this paper, a novel adaptive neurofuzzy inference system (ANFIS-based) approach to reconstruct kinematics of colliding vehicles is presented. A typical five-layered ANFIS structure is trained to reproduce kinematics (acceleration, velocity, and displacement) of a vehicle involved in an oblique barrier collision. Subsequently, the same ANFIS structure is applied to simulate different…
Determining the Parameters of a Sugeno Fuzzy Controller Using a Parallel Genetic Algorithm
2013
Developed in the mid 1970s, the technique based on genetic algorithms proved its usefulness in finding optimal or near optimal solutions to problems for which accurate solving strategies are either non-existent or require excessively long running time. We implemented a genetic algorithm to determine the parameters of a Sugeno fuzzy controller for the Truck Backer-Upper problem (This problem is considered an acknowledged benchmark in nonlinear system identification.). Less known at first than Mamdami fuzzy controllers, Sugeno fuzzy controllers became popular once they were included into the ANFIS neuro-fuzzy Matlab library. By their nature, Sugeno controllers can be regarded as interpolation…
Inverse kinematics of a 7 DOF manipulator using Adaptive Neuro-Fuzzy Inference Systems
2012
This paper was carried out objectively to explore and describe the inverse kinematics solutions of an anthropomorphic redundant robotic structure with seven degrees of freedom and human like workspace. Traditional inverse kinematics methods can have an unacceptably slow pace for the today's extremely redundant systems. The presented method uses the Adaptive Neuro-Fuzzy Inference Systems (ANFIS) editor and the Fuzzy Logic toolbox from MATLAB® which allow the investigation of various kinematical suitable solutions. ANFIS supports the determination of one degree of freedom, remaining therefore only six undetermined degrees. For better understanding of the simulations a CAD model that mimics th…
Adaptive neuro-fuzzy inference system for kinematics solutions of redundant robots
2016
This written paper presents aspects concerning the implementation of the Adaptive Neuro-Fuzzy Inference System (ANFIS) in the resolution of a redundant serial robot kinematics. The kinematics solutions are divided into two categories: direct kinematics solutions and inverse kinematics solutions. To be able to control a robot the most important solutions are the ones for the inverse kinematics since one knows the position and the final orientation of the end effector and needs to determine the relative displacement or movements into the robot couplings. To obtain the optimal solutions for the inverse kinematics of a redundant robot the mathematical equations were based onto the redundancy ci…