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IMAT3406 Fuzzy Logic Week 10PowerPoint Presentation

IMAT3406 Fuzzy Logic Week 10

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IMAT3406 Fuzzy Logic Week 10. Fuzzy Logic Applications. Fuzzy Logic Applications Digital Fuzzy Processor Omron was the first to launch a controller employing fuzzy logic for improved control and tuning Production of the world's fastest digital fuzzy processor (DFP) in 1990.

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### IMAT3406 Fuzzy LogicWeek 10

Fuzzy Logic Applications

Digital Fuzzy Processor

Omron was the first to launch a controller employing fuzzy logic for improved control and tuning

Production of the world's fastest digital fuzzy processor (DFP) in 1990.

Reasoning speed of 10 MFLIPS (1 Million Fuzzy Logic Inferences per second)

Input Variables for Fuzzy Logic Traffic Signal Controller

Maximum Queue Length (in metres): the distance in metres from the stop-line over which vehicles have queued

Average Occupancy Rate (%): percentage of time that the detection area was occupied by one or more vehicles.

Output Variable for the Controller

Weight[0, 100]: the degree of green traffic signal requirement

Applications of Fuzzy Logic to Traffic Signal Control

(Budi Yulianto, “Application of fuzzy logic to traffic signal control under mixed traffic conditions”, tec, October 2003, pp:332-335)

Improvement

(up to) 25% in average travel time

Rule Table/Matrix for Traffic Signal Control

Maximum Queue Length

Average Occupancy Rate

L: Low, VL: Very Low, VVL: Very Very Low,

M: Medium,

H: High, VH: Very High, VVH: Very Very High

use fuzdemos MATLAB function

- Ball Juggler
- Water Tank (Water Level Control)
- Controlling cart and pole
- Controlling ball and beam
- Backing truck

Live Demo

Fuzzy Washing MachineCamera AutofocusServo Motor Force ControlGlass Melting Furnace ControlAir Conditioner ControlReactor ControlCAR Automatic TransmissionsDisc Drive Spindle ServosFuzzy Automated ManufacturingTwo-Stage Inverted Pendulum

More fuzzy logic applicationshttp://www.aptronix.com/fuzzynet/index.htm

Fuzzy Logic applications in Bio-Health Informatics

- Intelligent Detection of abnormal neonatal cerebral heomodynamics
- Cancer prognosis
- Gene identification and gene network modelling

SIGNAL PROCESSING UNIT

FEATURE EXTRACTION UNIT

Neuro-Fuzzy System for Detection

Intelligent Detection of abnormal neonatal cerebral heomodynamics

- Normal baby

- Baby with severe birth asphyxia

Gene identification and gene network modelling

List of genes associated with diseases/condition

Fuzzy System

Gene networks

Fuzzy Logic Applications in MATLAB

- You can see a list of the applications in Fuzzy Logic Toolbox’s Demo. You will be shown a couple of them in the lecture. However, you are advised to go through all the applications provided in the toolbox’s demo
- They can be found at Help/Full Product Family Help/Demos/Toolboxes/Fuzzy Logic

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