Fuzzy Logic Control.

Presentasi berjudul: "Fuzzy Logic Control."— Transcript presentasi:

1 Fuzzy Logic Control

2 Sistem Kendali Kendali = pengukuran, penggerak (aktuator) dan prosesor
Video Pendulum Terbalik

3 Produk yg mendasarkan pada embedded control

4 Embedded control di sekitar kita

5 Inverted Pendulum

6

7 Siklus Desain Sistem Kendali
Pemilihan sensor & aktuator Pemodelan dinamik & simulasi open-loop Desain pengen-dali Simulasi closed-loop Implemen tasi real-time pengen- dali Hardware-in-the-loop simulation & rapid prototyping Uji eksperi men pd sistem fisik

8 CONVENTIONAL CONTROL Open-loop control is ‘blind’ to actual output
Closed-loop control takes account of actual output and compares this to desired output Measurement Desired Output + - Process Dynamics Controller/ Amplifier Output Input

9 Digital Control System Configuration

10 Fuzzy Control Fuzzy control provides a formal methodology for representing, manipulating, and implementing a human’s heuristic knowledge about how to control a system.

11 Fuzzy Systems Fuzzifier Inference Engine Defuzzifier Fuzzy
Input Fuzzifier Inference Engine Defuzzifier Output Fuzzy Knowledge base

12 Fuzzy Control Systems Plant Input Fuzzifier Inference Engine
Defuzzifier Plant Output Fuzzy Knowledge base

13 Basic configuration of fuzzy logic control system

14 Block diagram for a fuzzy inference system

15 Block diagram for a fuzzy inference system

16 The structure of a FKBC

17 Three fuzzy partition terms: N(Negative), Z(Zero), and P(Positive)

18 Rule Base Construction
Intuitive Method Method based Operator (Expert) Experience Response Ideal Method

19 Fuzzy decision rule justification by using step response

20 DML Rule Prototype with Three Fuzzy Set Term
(negative, zero, positive)

21 Rule Justification with Three Fuzzy Set Terms

22 Configuration Procedure and DML Consequence

23 Masukan kendali setelah tahap defuzzifikasi
(Masukan kendali C1: Metoda maksimum rata-rata Masukan kendali C2: Metoda pusat area)

24 Various defuzzification schemes for obtaining a crisp output.

25 Fuzzy Partition using Seven Terms

26 Fuzzy Rules with 7 Terms {NB, NM, NS, ZE, PS, PM, PB}

27 Tabel Justifikasi kaidah dengan tujuh subset fuzzy

28 The rule base of a PI-like FKBC in tabular form:
the five groups of rule

29 The Mamdani fuzzy inference system using min and max for T-norm
And T-conorm operators, respectively.