scholarly journals A simulation-implementation methodology of a fuzzy logic based control system

1997 ◽  
Vol 2 (1) ◽  
pp. 61-68
Author(s):  
Gilberto Costa Drumond Sousa ◽  
Bimal K. Bose ◽  
Marcelo Godoy Simões
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Implementation Methodology

Design and Simulation of Smart Control System for Internet Traffic Distribution on Servers by Using Fuzzy Logic System

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Raid Daoud ◽  
Yaareb Al-Khashab
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Input Parameter ◽  
Traffic Density ◽  
The Internet ◽  
Linguistic Variables ◽  
Internet Service ◽  
Traffic Distribution ◽  
Smart Control ◽  
High Level

The internet service is provided by a given number of servers located in the main node of internet service provider (ISP). In some cases; the overload problem was occurred because a demand on a given website goes to very high level. In this paper, a fuzzy logic control (FLC) has proposed to distribute the load into the internet servers by a smart and flexible manner. Three effected parameters are tacked into account as input for FLC: link capacity which has three linguistic variables with Gaussian membership function (MF): (small, medium and big), traffic density with linguistic variables (low, normal and high) and channel latency with linguistic variables (empty, half and full); with one output which is the share server status (single, simple and share). The proposed work has been simulated by using MATLAB 2016a, by building a structure in the Fuzzy toolbox. The results were fixed by two manners: the graphical curves and the numerical tables, the surface response was smoothly changed and translates the well-fixed control system. The numerical results of the control system satisfy the idea of the smart rout for the incoming traffics from the users to internet servers. So, the response of the proposed system for the share of server ratio is 0.122, when the input parameter in the smallest levels; and the ratio is 0.879 when the input parameters are in highest level. The smart work and flexible use for the FLC is the main success solution for most of today systems control.

Sistem Kontrol Optimal Fuzzy-Particle Swarm Optimization

2018 ◽  
Vol 9 (1) ◽  
pp. 1-5
Author(s):  
Fachrudin Hunaini ◽  
Imam Robandi ◽  
Nyoman Sutantra
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Control System ◽  
Membership Function ◽  
Fuzzy Logic Control ◽  
Particle Swarm ◽  
Optimization Method ◽  
Swarm Optimization ◽  
Motion Error ◽  
Logic Control

Fuzzy Logic Control (FLC) is a reliable control system for controlling nonlinear systems, but to obtain optimal fuzzy logic control results, optimal Membership Function parameters are needed. Therefore in this paper Particle Swarm Optimization (PSO) is used as a fast and accurate optimization method to determine Membership Function parameters. The optimal control system simulation is carried out on the automatic steering system of the vehicle model and the results obtained are the vehicle's lateral motion error can be minimized so that the movement of the vehicle can always be maintained on the expected trajectory

Permanent Magnet Chatter Absorber with Fuzzy Logic Control

2009 ◽  
Vol 147-149 ◽  
pp. 290-295 ◽  
Author(s):  
Bogdan Broel-Plater ◽  
Stefan Domek ◽  
Arkadiusz Parus
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Control ◽  
Fuzzy Logic Control ◽  
Control Algorithm ◽  
Permanent Magnets ◽  
Practical Experience ◽  
High Energy ◽  
Logic Control ◽  
Machine Operators

The paper deals with semi-active chatter absorber based on an electrodynamic transducer built around high-energy permanent magnets. Also, a fuzzy logic control system for the absorber control system has been designed. The principal advantage of fuzzy control is the possibility to implement practical experience gained by machine operators in the control algorithm. Hence, the possibility of factoring such quantities, as vibrations experienced by selected points of the machine-tool, and sound emitted by working machine into the analyzed chatter absorber fuzzy control system has been studied in the paper. The control system has been tested by way of simulation with the use of the process and cutting force models.

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