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An Auto-Tuning Method for the Scaling Factors of Fuzzy Logic Controllers with Application to SISO Mechanical System

Gamal Abdel Nasser, Abdel Badie Sharkawy, M-Emad S. Soliman
2015 International Journal of Materials Mechanics and Manufacturing  
In this paper, a PD-like self-tuning fuzzy controller based on tuning of scaling factors (STFC) by gradient descent method is presented.  ...  Index Terms-Fuzzy logic controller (FLC), scaling factors, gradient decent method, performance indices. Bratislava in 1999.  ...  The fuzzy system has three membership functions for each of the two inputs (e and ̇) and three membership functions for the output. The rule-base consists of 9 rules.  ... 
doi:10.7763/ijmmm.2015.v3.165 fatcat:h44taflm6vgwnb2fqi6adacx2y

Using Fuzzy Logic to reduce power consumption of notebooks

Ying-Wen Bai, Ciun-Hung Cheng
2009 2009 IEEE 13th International Symposium on Consumer Electronics  
These two parts cooperate to control the backlight brightness and the speed of the cooling fan, by using the fuzzy control rule as a replacement the traditional method.  ...  The fan speed is controlled by the CPU to maintain a constant temperature. The LCD backlight brightness which is based on the keystroke frequency or the touchpad is adjusted by using the FLC.  ...  The fuzzy rules for the control of temperature and fan are designed as follows: DL z THEN TL is x IF Rule DM z THEN TM is x IF Rule DS z THEN TS is x IF Rule = = = . 3 . 2 . 1 In the EC part we have added  ... 
doi:10.1109/isce.2009.5156815 fatcat:4qwieds5gjablbdxwoxdz2jkuu

Performance Evaluation of Automobile Fuel Consumption Using a Fuzzy-Based Granular Model with Coverage and Specificity

Yeom, Kwak
2019 Symmetry  
The method was augmented by the coverage and specificity of the GMs output as the performance index. For the GM validation, its performance was compared and analyzed using the auto MPG dataset.  ...  The predictive performance of different granular models (GMs) was compared and analyzed for methods that evenly divide linguistic context in information granulation-based GMs and perform flexible partitioning  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/sym11121480 fatcat:7n555nejebaijif3gajjjfikte

ENHANCEMENT OF FUZZY LOGIC CONTROLLER WITH RULE-VIEWER FOR RESTORATION SCHEME IN POWER SYSTEM

ArvindSingh Rathore, Amrit Ghosh, Prasun Chakrabarti
2016 International Journal of Advanced Research  
logic was conceived, namely, the realm of fuzzy logic based process control, as per today's world there are two types of control i.e.  ...  Fuzzy control is based on an I/O function that maps each very low-resolution quantization interval of the input domain into a very low-low resolution quantization interval of the output domain.  ...  There are several methods to design a fuzzy controller. The design of fuzzy controller involves formation of membership function and rule base.  ... 
doi:10.21474/ijar01/768 fatcat:n3irdwh5t5cixbhvdinx4xekgm

A Learning Algorithm for Distance-type Fuzzy Reasoning Method

Shuoyu WANG, Takeshi TSUCHIYA, Masaharu MIZUMOTO
2000 International journal of biomedical soft computing and human sciences  
Tlie distance-type fuzzy reasoning method auto-tuning methods [3 5] based on the delta nile, which is a simplified reasoning method [2] , have been proposed.  ...  By the learning axioms, the leaming algoritlmi based on the decomposition characteristic of the distance-type fuzzy reasoning method consists of the fo11owing five steps.  ... 
doi:10.24466/ijbschs.6.1_61 fatcat:xgsihybjevahvly3glmww5qddq

A Hybrid CBR Model for Forecasting in Complex Domains [chapter]

Florentino Fdez-Riverola, Juan M. Corchado
2002 Lecture Notes in Computer Science  
The proposed model employs a case-based reasoning system to wrap a growing cell structures network, a radial basis function network and a set of Sugeno fuzzy models to provide an accurate prediction.  ...  In situations in which the rules that determine a system are unknown, the prediction of the parameter values that determine the characteristic behaviour of the system can be a problematic task.  ...  Similar fuzzy sets for one parameter are merged to create a common fuzzy set to replace them in the rule base.  ... 
doi:10.1007/3-540-36131-6_11 fatcat:6vlpcf2cavfw3dfy7wtpopexyu

An Automated Hybrid CBR System for Forecasting [chapter]

Florentino Fdez-Riverola, Juan M. Corchado, Jesús M. Torres
2002 Lecture Notes in Computer Science  
The proposed system employs a case-based reasoning model that incorporates a growing cell structures network, a radial basis function network and a set of Sugeno fuzzy models to provide an accurate prediction  ...  In situations in which the rules that determine a system are unknown, the prediction of the parameter values that determine the characteristic behaviour of the system can be a problematic task.  ...  Similar fuzzy sets for one parameter are merged to create a common fuzzy set to replace them in the rule base.  ... 
doi:10.1007/3-540-46119-1_38 fatcat:2blr7dpforbl3iarybqmexslgy

FSfRT: FORECASTING SYSTEM FOR RED TIDES. A HYBRID AUTONOMOUS AI MODEL

F. FDEZ-RIVEROLA, J. M. CORCHADO
2003 Applied Artificial Intelligence  
Hybrid reasoning system, neural indexing, neural adaptation, extracting fuzzy rules, fuzzy revision, forecasting red tides.  ...  Statistical models such as Auto-Regressive Integrated Moving Averages (ARIMA) have been applied, but the results obtained so far have indicated that they have less facility for forecasting such parameters  ...  , 1985) , which is generated from the trained RBF network and provides the basis for the creation of a fuzzy rule-based revision subsystem.  ... 
doi:10.1080/714858319 fatcat:qxnfbwtq7vhjdjodpusqyuvzs4

Research on Auto-Scaling of Web Applications in Cloud: Survey, Trends and Future Directions

Parminder Singh, Pooja Gupta, Kiran Jyoti, Anand Nayyar
2019 Scalable Computing : Practice and Experience  
One of the key challenges for web application in cloud computing is auto-scaling.  ...  Based on the analysis, we proposed the new areas of research in this direction.  ...  The fuzzy rule-based model used to construct the auto-scaler.  ... 
doi:10.12694/scpe.v20i2.1537 fatcat:5zdylggvtjdslichn6mpoleese

Advanced Automatic Pumping Station with Canal Level Remote Control System Using ABB PLC Based on FLC

Muhammad ISHTIAQ, Zhan-Ming LI
2017 DEStech Transactions on Engineering and Technology Research  
The applied control method is based on Fuzzy Logic System, designed in MATLAB -Simulink, which can communicate with PLC through OPC server by using gateway.  ...  The system is designed for the agricultural land where the water level (i.e. canals or rivers) is low and traditional system of irrigation is not working well.  ...  FLC Method The main principle components for fuzzy logics are fuzzifier, rule base and inference engine and defuzzifier.  ... 
doi:10.12783/dtetr/icca2016/5975 fatcat:3rjxr2h62zgplesbtb55posomq

A Novel Robot Motion Planning Model Based on Visual Navigation and Fuzzy Control

Xiaomin Wang
2017 DEStech Transactions on Social Science Education and Human Science  
In this paper, we propose the novel robot motion planning model based on the visual navigation and fuzzy control.  ...  this fuzzy control technology theory, known as the fuzzy control theory.  ...  some difficulties; Second, if there is not enough input and output data, these networks simply cannot work before the training that creates the fuzzy control rule and the revision rule according to the  ... 
doi:10.12783/dtssehs/asshm2016/8380 fatcat:skjux22e6fhg7cdlkbboo7irg4

Automatic tuning of myoelectric prostheses

C Bonivento, A Davalli, C Fantuzzi, R Sacchetti, S Terenzi
1998 Journal of rehabilitation research and development  
The software package, Microprocessor Controlled Arm (MCA) Auto Tuning, is a tool for aiding both INAIL expert operators and unskilled persons in the controller parameter tuning procedure.  ...  The package core consists of Fuzzy Logic Expert Systems (FLES) that embody skilled operator heuristics in the tuning of prosthesis control parameters.  ...  Fuzzy methods in expert systems for 1. Hogan N . A review of the methods of processing EMG for configuration and control .  ... 
pmid:9704313 fatcat:ywqmp3mvp5fxra5ppqnaxqwqv4

Time series prediction of apple scab using meteorological measurements
English

Cetişli Bayram, Buuml yuuml kccedil ingir Eşref
2013 African Journal of Biotechnology  
A new prediction model for the early warning of apple scab is proposed in this study. The method is based on artificial intelligence and time series prediction.  ...  The important hours of duration were determined with the feature selection methods, such as Pearson's correlation coefficients (PCC), Fisher's linear discriminant analysis (FLDA) and an adaptive neuro-fuzzy  ...  ACKNOWLEDGEMENT We thank Isparta Provincial Directorate of Agriculture for experimental dataset.  ... 
doi:10.5897/ajb12.394 fatcat:tg56y3fgfrhifmym7vuxogmvbi

FSfRT: Forecasting System for Red Tides

Florentino Fdez-Riverola, Juan M. Corchado
2004 Applied intelligence (Boston)  
The system employs a case-based reasoning model to wrap a growing cell structures network, a radial basis function network and a set of Sugeno fuzzy models to provide an accurate prediction.  ...  In situations in which the rules that determine a system are unknown, the prediction of the parameter values that determine the characteristic behaviour of the system can be a problematic task.  ...  Similar fuzzy sets for one oceanographic parameter are merged to create a common fuzzy set to replace them in the rule base.  ... 
doi:10.1023/b:apin.0000043558.52701.b1 fatcat:ztywyqfcnrhy3a2vw5wkjktrby

State Space Modeling and Short-Term Traffic Speed Prediction Using Kalman Filter Based on ANFIS

Nasim Barimani, Behzad Moshiri, Mohammad Teshnehlab
2012 International Journal of Engineering and Technology  
Using this method, KF will be applied to the nonlinear system so Jacobian computations of Extended Kalman Filter (EKF) that is essential for nonlinear systems are not needed.  ...  Another advantage of suggested method is that there is no need to design different ANFIS structure for different predict horizons in order to obtain acceptable prediction accuracy, because the error due  ...  The ANFIS has five layer structure shown in Fig. 2 . For simplification, we assume the ANFIS has only two inputs and one output and two fuzzy if-then rules.  ... 
doi:10.7763/ijet.2012.v4.330 fatcat:f4tao5zi5fgvzm3mh4iblcszu4
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