A 12b general-purpose fuzzy logic controller chip

1996 ◽  
Vol 4 (4) ◽  
pp. 460-475 ◽  
Author(s):  
H. Eichfeld ◽  
T. Kunemund ◽  
M. Menke
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
General Purpose

scholarly journals Disturbance Compensation in Fuzzy Logic Control of Level in Carbonisation Column for Soda Production

2020 ◽  
Vol 15 ◽  
Keyword(s):  
Fuzzy Logic ◽  
High Performance ◽  
Fuzzy Logic Controller ◽  
General Purpose ◽  
Rule Base ◽  
Disturbance Compensation ◽  
Real Time Control ◽  
System Error ◽  
Model Free ◽  
Time Control

The intelligent approaches emerge as leading techniques in providing of stable and high performance control of industrial plants with nonlinearity, model uncertainty, variables coupling and disturbances. In the present research a novel approach for the design of a nonlinear model-free fuzzy logic controller (FLC) with two inputs – the system error and the main measurable disturbance and a rule base for disturbance compensation is suggested. It is based on off-line parameter optimisation via genetic algorithms. The approach is applied for the development of a FLC for the control of the level of ammonia brine solution in a carbonisation column with compensation of the changes in the inflow pressure. The control algorithm is implemented in a general purpose industrial programmable logic controller in ”Solvay Sodi” SA – Devnya, Bulgaria. The FLC system with disturbance compensation outperforms in an increased dynamic accuracy the FLC with the system error as a single input even when linear feedforward disturbance compensation is added. The performance of all systems is assessed from the real time control and the simulations based on a derived TSK plant model.

scholarly journals Direct Torque Control of Doubly Star Induction Motor Using Fuzzy Logic Speed Controller

2018 ◽  
Vol 7 (1) ◽  
pp. 42
Author(s):  
Lallouani Hellali ◽  
Saad Belhamdi
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Controller ◽  
Direct Torque Control ◽  
Pi Controller ◽  
General Purpose ◽  
Torque Control ◽  
Speed Controller ◽  
Wide Range ◽  
Time Required

<p>This paper presents the simulation of the control of doubly star induction<br />motor using Direct Torque Control (DTC) based on Proportional and Integral<br />controller (PI) and Fuzzy Logic Controller (FLC). In addition, the work<br />describes a model of doubly star induction motor in α-β reference frame<br />theory and its computer simulation in MATLAB/SIMULINK®.The structure<br />of the DTC has several advantages such as the short sampling time required<br />by the TC schemes makes them suited to a very fast flux and torque<br />controlled drives as well as the simplicity of the control algorithm.the<br />general- purpose induction drives in very wide range using DTC because it is<br />the excellent solution. The performances of the DTC with a PI controller and<br />FLC are tested under differents speeds command values and load torque.</p>

Application Fuzzy Logic System for Accurate Sheet Trim Shower Position

2019 ◽  
Vol 3 (1) ◽  
pp. 186-192
Author(s):  
Yudi Wibawa
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Dc Motor ◽  
Automation System ◽  
Paper Making ◽  
System A ◽  
Accurate Position ◽  
And Performance ◽  
Better Than ◽  
Logic System

This paper aims to study for accurate sheet trim shower position for paper making process. An accurate position is required in an automation system. A mathematical model of DC motor is used to obtain a transfer function between shaft position and applied voltage. PID controller with Ziegler-Nichols and Hang-tuning rule and Fuzzy logic controller for controlling position accuracy are required. The result reference explains it that the FLC is better than other methods and performance characteristics also improve the control of DC motor.

STABILISASI TEGANGAN KELUARAN BUCK CONVERTER DENGAN METODE FUZZY LOGIC CONTROLLER

JURNAL ELTEK ◽  
2018 ◽  
Vol 16 (2) ◽  
pp. 125
Author(s):  
Oktriza Melfazen
Keyword(s):  
Fuzzy Logic ◽  
Steady State ◽  
Rise Time ◽  
Fuzzy Logic Controller ◽  
Buck Converter ◽  
Settling Time

Buck converter idealnya mempunyai keluaran yang stabil, pemanfaatandaya rendah, mudah untuk diatur, antarmuka yang mudah dengan pirantiyang lain, ketahanan yang lebih tinggi terhadap perubahan kondisi alam.Beberapa teknik dikembangkan untuk memenuhi parameter buckconverter. Solusi paling logis untuk digunakan pada sistem ini adalahmetode kontrol digital.Penelitian ini menelaah uji performansi terhadap stabilitas tegangankeluaran buck converter yang dikontrol dengan Logika Fuzzy metodeMamdani. Rangkaian sistem terdiri dari sumber tegangan DC variable,sensor tegangan dan Buck Converter dengan beban resistif sebagaimasukan, mikrokontroler ATMega 8535 sebagai subsistem kontroldengan metode logika fuzzy dan LCD sebagai penampil keluaran.Dengan fungsi keanggotaan error, delta error dan keanggotaan keluaranmasing-masing sebanyak 5 bagian serta metode defuzzifikasi center ofgrafity (COG), didapat hasil rerata error 0,29% pada variable masukan18V–20V dan setpoint keluaran 15V, rise time (tr) = 0,14s ; settling time(ts) = 3,4s ; maximum over shoot (%OS) = 2,6 dan error steady state(ess) = 0,3.

Performance Comparison of MANET, VANET and FANET

2018 ◽  
Vol 8 (5) ◽  
pp. 132
Author(s):  
Aarti Sahu ◽  
Laxmi Shrivastava
Keyword(s):  
Fuzzy Logic ◽  
Wireless Network ◽  
Packet Loss ◽  
Ad Hoc Network ◽  
Fuzzy Logic Controller ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Performance Comparison ◽  
Fuzzy Rules ◽  
Mobile Ad Hoc

A wireless ad hoc network is a decentralized kind of wireless network. It is a kind of temporary Computer-to-Computer connection. It is a spontaneous network which includes mobile ad-hoc network (MANET), vehicular ad-hoc network (VANET) and Flying ad-hoc network (FANET). Mobile Ad Hoc Network (MANET) is a temporary network that can be dynamically formed to exchange information by wireless nodes or routers which may be mobile. A VANET is a sub form of MANET. It is an technology that uses vehicles as nodes in a network to make a mobile network. FANET is an ad-hoc network of flying nodes. They can fly independently or can be operated distantly. In this research paper Fuzzy based control approaches in wireless network detects & avoids congestion by developing the ad-hoc fuzzy rules as well as membership functions.In this concept, two parameters have been used as: a) Channel load b) The size of queue within intermediate nodes. These parameters constitute the input to Fuzzy logic controller. The output of Fuzzy logic control (sending rate) derives from the conjunction with Fuzzy Rules Base. The parameter used input channel load, queue length which are produce the sending rate output in fuzzy logic. This fuzzy value has been used to compare the MANET, FANET and VANET in terms of the parameters Throughput, packet loss ratio, end to end delay. The simulation results reveal that usage of Qual Net 6.1 simulator has reduced packet-loss in MANET with comparing of VANET and FANET.

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