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• Rendang

• 'West Sumatran caramelized beef curry‘. In 2011 an online poll by 35,000 people held by CNN International chose Rendang as the number one dish of their 'World’s 50 Most Delicious Foods list. (http://en.wikipedia.org/wiki/Rendang)

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Teaching Activity

Industrial Automation Workshop

PLC-based Automation

Microcontroller, Mechatronics/Robotics

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Professional Course

PLC-based Automation Upgrading course for Vocational High School Teacher.

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Professional Course

Governor Automatic Control and SCADA OJT for State Electricity Company Employee

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Research Activity• Decision Making Algorithm on Keeper Robot soccer.

Indonesian Symposium on Robot Soccer Competision. ISRSC (2013)

• PC-based identification and PID controller Design for Temperature Process Control Trainer (2010-2011)

• Implementation of Fuzzy Logic for tuning PI controller in Motor DC speed control system (2009)

• Design and Implementation of Robust Cascade Controller for Pressure Control Trainer (Feedback 38-714). (2008)

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Design and Implemetation of Robust Cascade Controller Design and Implemetation of Robust Cascade Controller for Pressure Control Trainer (Feedback 38-714).for Pressure Control Trainer (Feedback 38-714).

ABSTRACTABSTRACT

This research aim to design and implement cascade controller in pressure control trainer, Feedback 38-714. The device has been equipped with PID controller which is a single-loop controller structure applied widely in industry. The controller is easily implemented and relatively easy in tuning. However, in the other hand, it is unable to reduce load disturbance effect. In process control system, load disturbance becomes a main problem. Cascade control can be used to overcome the problem. To guarantee closed-loop system stability while plant parameters changing happen due to load disturbance, the cascade controller is designed to achieve robust H-infinity criterion.

Cascade control design in this research uses classical method approach. The objective design is to guarantee closed-loop system stability and performance while load disturbance occurs. The controller gained is simulated and implemented to the real plant Pressure Control Trainer (Feedback 38-714).

The simulation result shown that design of closed-loop system has achieved robust stability criteria based on small gain theorem. So, the system stability can be guaranteed due to plant parameters changing. The implementation result shown that closed-loop system was able to reach set-point while plant parameters changing happen due to load disturbance.

Key words : cascade control, H-infinity, pressure control trainer, robust, uncertainty

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IntroductionWide application of ELECTRO-PNEUMATIK System in Industry• Explosive resistant• Simplicity• Easy Maintenance

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Technology Performance Plant parameters changes stability Load changes stability Steady-state error ≈ 0 Overshoot ≈ 0

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single loop Structure of PID controllerProportionalProportionalIntegralIntegralDifferentialDifferential

Industrial automation standard, because the benefits are easy to implement and relatively easy to be tuned

The disadvantage • unable to eliminate disturbances• unable to maintain the desired criteria on various

system parameter changes.

Introduction…

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Cascade control StructureCascade control Structure• Effective for disturbances reductionEffective for disturbances reduction• Improve response system performanceImprove response system performance

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Problem

Plant parameter ChangesPlant parameter Changes Model UncertaintiesModel Uncertainties

Solutions

Robust Cascade Robust Cascade ControlControl

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Research aims:

Design interface circuit for model identification and control Obtain model of Pressure Control Trainer Feedback 38-714

with model identification Design cascade controller refer to robust H-infinity criteria Controller Implementation to Pressure Control Trainer

(Feedback 38-714) Robustness Analysis of closed-loop respon system to plant

parameter changes

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Industrial standard component

signal conditioning (output:4-20mA) for each sensors

equipped with Pressure Sensor and Differential pressure sensor

Pressure Control Trainer (Feedback 38-714)Pressure Control Trainer (Feedback 38-714)

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Struktur Kontrol Kaskade

• Tujuan kontroler kaskade (Luyben,1997):– Mengeliminasi pengaruh gangguan– Meningkatkan performansi sistem kontrol

• Requirement : inner loop respons >> outer loop respons

Gc1(s) G2(s) G1(s)-+ +

+

++

d2 d1

r2r1 e1 e2 u y2 y1

-+

Inner loop

Gc2(s)

Master / primaryMaster / primaryControllerController

auxiliary / auxiliary / secondarysecondaryControllerController

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Robust Control (1)• Adanya ketidak pastian dalam pemodelan• Adanya perubahan parameter plant:

– Akibat usia pemakaian– Karena variasi operasional

• Obyektif Kontrol:– Sistem tetap kokoh dalam perubahan dinamika plant– Sistem tetap stabil dalam perubahan parameter plant– Memiliki gain tinggi pada frekuensi rendah setelah itu gain

kontroler turun dengan cepat setelah mencapai frekuensi crossover.

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Robust Control (2)• Uncertainty:

– Additif:• Parallel dengan model nominal• Untuk uncertainty pada frekuensi tinggi• G + ∆

– Multiplicative:• Seri dengan model nominal• Untuk uncertainty pada frekuensi rendah• G ( I + ∆ ) = G + G∆

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Robust Control (3)

121

112122 )(),( MMIMMMFU

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• LFT (linear fractional transformation)– Untuk memodelkan variasi plant sebagai variabel gain linier

pada suatu feedback– Untuk memetakan ketidakpastian real plant ke dalam

kerangka matematik sistem linier• Upper LFT

• Lower LFT

211

221211 )(),( MMIKMMKMFL

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Design procedures:

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Load various:

PROCESS

FTFC

PrTPrC

control valve

airsupply

SP

auxiliary controller

airreceiver

V1

V2

V3

V4

V5

V6

I/P

Normal Load:Normal Load:

V4 open, V5 V4 open, V5 openopen

V6 closedV6 closed

Max Load:Max Load:

V4 open, V5 V4 open, V5 openopen

V6 openV6 open

Min Load:Min Load:

V4 open,V5 V4 open,V5 closedclosed

V6 closedV6 closed

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Identification dan Controling diagram

ComputerPressure Control Trainer Feedback 38-714

ADC

I/V converter

DAC

I/V converter

menujuI/P converter

dari sensor tekanan

dari sensor laju aliran

V/I converter

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Pressure Transmitter(Feedback 38-461)

Diff PressureSensor

PressureSensor

Diff Pressure Transmitter

(Feedback 38-462)

ADC

I/VConverter

I/VConverter

DACV/I

ConverterI/P Converter

(Watston Smith 100x)Pneumatic Valve(Platon M Valve)

DB25

Parallel port

PC

Process Control Adapter

.

.

.

4-20 mA

4-20 mA

4-20 mA 3-15 psi

0-5 V

0-5 V

0-5 V

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Model Identification

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Laod

Model TFTekanan (pressure)

GM1(s)Laju aliran (flow rate)

GM2(s)

Normal

Max

Min

Model Plant TF Table from IdentificationModel Plant TF Table from Identification

4,375

18,2622

ss

s

7,266

98,12,612

ss

s

3,484

38,28,622

ss

s

138

27,1

s

130

86,0

s

146

78,1

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Ketidakpastian Parameter Plant

1)(1

s

ksGM

78,186,0 k4630

(nominal 1,27)

(nominal 38)

122

3

122 )(

asasa

bsbsGM

8,622,61 2 b

38,298,1 1 b

8466 2 a

3,47,2 1 a

(nominal 62)

(nominal 2.18)

(nominal 75)

(nominal 3.4)

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State Space Model with Uncertainty (1)

ky2

-

+ 1τ ∫

x x y1=)1( p )1( kkpkk

ModelModel for pressure plant for pressure plant

Mky2 -+ xMτi

δkuk

yk

vk

δτuτ yτx y1=

1

1

p

pM i

kp

kM

k

k

0

2

1

1

1 0001

000

y

u

u

x

k

p

p

y

y

y

x

k

kp

kp

k

k

k

22212

12111

21

DDC

DDC

BBA

G pres

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State Space Model with Uncertainty (2)

ModelModel for flowrate plant for flowrate plant

b1u

-+ ∫

1xb2

∫2x=2x

+

+

a1

a2+

+

x1 y2=

u -+ 1x 2x=2x

+

+

+

+ Ma2

δa2

Mb1

δb1ub1

yb1

δb2

Ma1

δa1

Mb2

ub2yb2

va1

vb2

va2

ya2

ya1

ua2

ua1

x1 y2=

),()1( 222222 bbU MFbpbbb ),()1( 111111 bbU MFbpbbb ),()1( 222222 aaU MFapaaa

),()1( 111111 aaU MFapaaa

22

22

0

bp

bM

bb

11

11

0

bp

bM

b

b

22

22

0

ap

aM

aa

11

11

0

ap

aM

aa

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u

u

u

u

u

x

x

a

a

b

b

bpppaa

bp

y

y

y

y

y

x

x

a

a

b

b

aab

b

a

a

b

b

1

2

1

2

2

1

1

2

1

2

112121

22

2

1

2

1

2

2

1

0000001

000000

000000

000000

000000

0

00010

22212

12111

21

DDC

DDC

BBA

G flow

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Weighting Function (1) Choosen value refer to open-loop plant Characteristic in

Frequency Domain

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Weighting Function (2)Pressure plant performance WF (wPressure plant performance WF (wpppp))

Flowrate plant performance WF (wFlowrate plant performance WF (wpfpf))

01,04,11

8,1296,0)(

2

2

ss

ssswpp

92

2

10

12231,0)(

ss

ssswpf

“ Note that finding appropriate weighting functions is a crucial step in robust control design and usually needs a few trials. For

complex systems, significant efforts may be required ” (Gu, 2005)

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Augmented plant

Gpres

∆

Wpp

-Wup

Gc+- ++

G

r = 0 u

depp

eup

Gflow

∆

Wpf

-Wuf

Gc+- ++

G

r = 0 u

depf

euf

Pressure plantPressure plant

Flowrate plantFlowrate plant

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Controller Parameter

Primary Controller

0,00328 3,75s s73,11s

0,4608 17,51s 0,0006262s 23

2

presGc

Secondary Controller

007-1,785e 90,34s 165,5s 77,16ss

114,6 2590s s1407s 18,3234

23

flowGc

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Result and analysis

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Control System overall Block Diagram

Gcpres(s) Gpres(s)CV1SP e1 e2

Inner loop

Gcflow(s) Gflow(s)PV1

-+ -+ PV2CV2

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0,00328 3,75s s73,11s

0,4608 17,51s 0,0006262s 23

2

presGc

007-1,785e 90,34s 165,5s 77,16ss

114,6 2590s s1407s 18,3234

23

flowGc

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WF dan closed-loop sensitivity assessment(1)

• Inner loop

12 )()( GcGIGS flowflow

,)(

1)(

jwjS

P

1,1

SwSw PP

||wpfS||∞ = 0.7531 < 1

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WF dan closed-loop sensitivity assessment (2)

• Outer loop

,)(

1)(

jwjS

P

1,1

SwSw PP

||wppS||∞ = 0.9854 < 1

11)()( GcGIGS prespres

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Simulation Results (1)

Inner loop respons with secondary controller

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Simulation Results (2)

Outer loop responsewith primary controller

System response withCascade controller

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Implementation flowchart

0,00328 3,75s s73,11s

0,4608 17,51s 0,0006262s 23

2

presGc

mulai

err_1 = SP – PV1

output sinyal kontroler primer ke inner loop (CV1)

selesai

persamaan beda kontroler primer

masukkan nilai SP

inisialisasi parameter kontroler

baca sensor pressure (PV1)

err_2 = CV1 – PV2

output sinyal kontroler sekunder ke plant (CV2)

persamaan beda kontroler sekunder

stop?tidak

ya

baca sensor flowrate (PV2)

time samplingTs = 1,66 detik

time samplingTs = 0,2 detik

3)-X(k 0,080132)-X(k 761,11)-X(k 927,1

3)-Y(k 009-3.495e 2)-Y(k 5795,01)-Y(k 579,1Y(k)

009-3.495e z 0,5793 + z 1,579 - z

0,08013 - z 1,761 - z 1,927)(

23

2

zK pres

4)-005X(k-6,472e 3)-X(k 27,22)-X(k 5,466-1)-X(k 198,3

4)-Y(k007293,93)-0,674Y(k2)-Y(k316,21)-Y(k 2,642 Y(k)

e

007-9,293e + z 0,674 - 6z 2,31 + z 2,642 - z

005-6,472e z 2,276 + z 5,466 - z 3,198)(

234

23 zK flow

007-1,785e 90,34s 165,5s 77,16ss

114,6 2590s s1407s 18,3234

23

flowGc

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Implementation Respons System (1)

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Laod = N-Max-N Load = N-Min-N

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Implementation Respons System(2)

Load = N-Max-Min

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Respon inner loop hasil implementasi (1)

Laod = N-Max-N Load = N-Min-N

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Respon inner loop hasil implementasi (2)

Load = N-Max-Min

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Conclusion

The results of closed-loop design with cascade control in this research, are qualified robust stability and robust performance based on the small gain theorem, so that the stability and performance of the system can be maintained in the event of changes in plant parameters

Classical methods approach can be used to design a robust cascade controller. Thus, resolving can use SISO (single input single output) system calculation.

Implementation result shows good achievement. Thus, performance robustness and stability robustness can be maintained in the event of changes in plant parameters

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44.8076701

70.7640521

116.6148861

11.6456191

-10

10

30

50

70

90

110

130

no

rm e

rro

r

orde1 orde2 orde3 orde1-modified

138

27,1)(

ssGpres

Model Plant Tekanan dan Validasi

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234.96791 234.41089 233.11072

17.3011

-25

25

75

125

175

225

275

no

rm e

rro

r

orde1 orde2 orde3 orde-modified

4.375

18,262)(

2

ss

ssG flow

Model Plant laju aliran dan Validasi

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Small Gain Theorem

Asumsikan G1 , G2 H∞ keduanya stabil, bounded-gain transfer function.Jika ||G1G2||∞ < 1, sistem closed-loop stabil.

Selanjutnya, karena ||G1G2||∞ < ||G1||∞ ||G2||∞ lalu jika ||G1||∞ ||G2||∞ < 1, sistem closed-loop stabil

G1

G2

e1+

+e2u2

y1

y2

u1

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Vektor Norm Matrix Norm

n

iixx

11

n

iixx

1

2

2

ii

xx max

m

iij

jaA

11

max

n

jij

iaA

1

max

AA 2

53

“Matlab-Simulink” Simulation

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Tabel Performansi Sistem Terhadap Perubahan Beban

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Karakteristik V/I dan I/V konverter

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