AFM10 datasheet(2/4 Pages) STMICROELECTRONICS

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LEARNING

it is composed by two phases:

BUILDING RULES It allows to perform the auto-

matic selection of inference rules or their manual

definition, taking in to account the project con-

strains read from the previously opened pattern file.

As a result the user will be supplied with a rule file

containing the linguistic expression of the rules. An

unsupervised clustering algorithm is used to per-

form this task.

BUILDING MEMBERSHIP FUNCTIONS It allows

the user to select the membership function shape

and the fuzzy intference method for the project

elaboration.

Starting from the rule file supplied by the previous

phase, it initially associates to each fuzzy set a

standard membership function shape. These

shapes can be gradually tuned in order to let the

fuzzy system to better approximate the proc-

ess/function sampling by means of subsequently

run sessions. Back-propagation algorithm with

automatic learning rate control is used to this aim.

TOOLS

It is composed of different sub-menus:

LOCAL RULES it allows to add new rules to the

fuzzy logic knowledge base determined by an

Adaptive Fuzzy Modeller run session. Aim of this

functionality is the local approximation level im-

provement.

SIMULATION it allows to simulate the fuzzy system

behaviour in order to verify the approximation level

obtained during the learning phase. The simulation

can be carried out in two different ways.

Simulation Step-by-Step: the user must supply

the simulator with the values variables correspond-

ing to the point to verify.

Simulation from File: the user must supply the

simulator with the name of a process/function

stream file that will be used to perform a complete

process inference.

VIEW FEATURES

View Features of the AFM gives with the capability

to visualize the fuzzy model extracted for a particu-

lar project. It allows a separate visualization of the

rules of inference and membership functions. The

rules can be visualized in a linguistic format. For

the membership functions you can choose

between a linguistic and a graphical format

visualization.

EXPORTERS

The Exporter provides library functions working

on the databases automatically generated, which

appropriately describe the data structures of the

selected project in terms of a different program-

ming environment.

These functions can be exploited inside the user’s

programs in order to verify the model extracted and

to use it in real application.

SUPPORTED TARGETS

The supported environment are:

- W.A.R.P.1.1 using FUZZYSTUDIO

™1.0

- W.A.R.P.2.0 using FUZZYSTUDIO

™2.0

- MATLAB

- C Language

- Fu.L.L. (Fuzzy Logic Language).

Learning

Phases

pattern file

Fuzzy Logic

knowledge base

Simulation

and Manual

Tuning

exporter to

processor

W.A.R.P. 1.1

W.A.R.P. 2.0

ANSI C

MATLAB

Rules

extractor

MFs

tuning

rules

minimizer

Figure 2. AFM Logic Flow.

Figure 3. BUILD MEMBERSHIP FUNCTION

window

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ADAPTIVE FUZZY MODELLER 1.0

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