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Sébastien Cabaret - October 20072
Overview
Regulation: what is a control loop? What is a PID controller? What is advanced control? Identifying, Modeling …. Tuning Advanced control example: predictive control Schneider tool for Modeling and Tuning
available in ITCO Application for GCS: MultiController
Sébastien Cabaret - October 20073
Regulation: what is a control loop?
“I want to see a measured value which corresponds to my request”
Sébastien Cabaret - October 20074
Regulation: what is a control loop?
Reaction:The water temperature reacts
on heating power changesTemperature
SensorTE
Controller or human!
Acts on heating power (4-20mA)
(0-500W)
DesiredTemperature
(ex: 150C)
Sébastien Cabaret - October 20075
Regulation: what is a control loop?
Control Loop system Representation Example: Open Loop representation
Sébastien Cabaret - October 20076
Regulation: what is a control loop?
Control Loop system Representation Example: Closed Loop representation
Sébastien Cabaret - October 20077
Reaction:The water temperature reacts
on heating power changesTemperature
Sensor (y)TE
C(p)Acts on heating power
(u, 4-20mA)
Desired Temperature(SP, 150C)
G(p)
Sébastien Cabaret - October 20078
What is a PID controller?
PID means Proportional, Derivative Integrative. In a classic control loop system, the PID is the controller placed
before the process:
Sébastien Cabaret - October 20079
What is a PID controller?
PID Elementary actions Proportional
KpCP )(
Sébastien Cabaret - October 200710
What is a PID controller?
PID Elementary actions Integrative
Ti is the coefficient given to increase or decrease the integrative action
pTpC
iI .
1)(
Sébastien Cabaret - October 200711
What is a PID controller?
PID Elementary actions Derivative
Td is the coefficient given to increase or decrease the derivative action
pTpC dD .)(
Sébastien Cabaret - October 200713
What is advanced control?
Advanced Control - Sébastien Cabaret – 9 Feb. 2006
Basic corrections PID
Other strategies
Advanced strategies
GPC, PFC, RST, IMC…
Others
Fuzzy, Neuronal network, …
Need for process identification
System complexity
Advanced Control
Sébastien Cabaret - October 200714
Identifying, Modeling… Tuning
Process to tune a controller We should have the knowledge of the system We should give information to the controller for its tuning
System information
Controller parametersTUNING
Ex: P,I and D for PID
Data acquisitionIdentification Modeling
Methods
Sébastien Cabaret - October 200715
Advanced control example: predictive control
The predictive control method is an advanced control strategy It is a good compromise between performance and
complexity It is based on a model for the prediction of the process
output and on a determinate horizon It also uses a reference trajectory to attempt the desire
response
Several predictive controls exist due to various mathematical approaches of automation people.
Sébastien Cabaret - October 200716
The predictive control is closed to human driver behavior
The controller contains the model of the process to drive
The model allows to predict the effect of the action to the system output
The driver has built a «mental picture» of its car behaviors
He knows the efficiency of the brakes and knows the effect to his car
A process model is integrated into the controller
SetPoint
The controller has the system knowledge and is able to calculate future action to have a desire output behavior
Action
Process
Output
Sébastien Cabaret - October 200717
The model used by the controller is a dynamic representation of the input/output relationships (ex: mental model of the car vs. the road)
The reference trajectory is known by the controller (ex: car trajectory)
The horizon definition is specified (ex: 20 seconds)
Predictive Control
Sébastien Cabaret - October 200720
Schneider tool for Modeling and Tuning available in ITCO
Optireg
•Schneider PLC •Some predictive algorithms
•PID
DataStore
Sébastien Cabaret - October 200721
Application: MultiController object in GCS project
EN
TR
Ramp
LimHSPLimLSP
MRegSel
Scaling
FromOutO
ManReg01
AuAuMoRMPosVal
MPTSel
IoSimu
MPRSel
RA
MPBSel
AuSPo
TRVal
AuRegR
MSPo
MPTime
IoError
RCPY
Param
AuRegSel
AuPosVal
LimLO
MV
LimHO
MPReal
EnRcpy
ENO
IoSimuW
LimHSPStLimLSPSt
StsReg01
AuPosVSt
FoMoStRegSt
MVSt
IoErrorW
AuMoSt
RegSelSt
TRSt
ScalingSt
AuSPoSt
OutOD
ParamSt
SPoSt
MMoSt
LimLOSt
OutO
LimHOSt
PosValSt
FBI_1
MultiController14
Sébastien Cabaret - October 200722
Application: MultiController object in GCS project
TR
Ramp
LimHSPLimLSP
MRegSel
Scaling
FromOutO
ManReg01
AuAuMoRMPosVal
MPTSel
IoSimu
MPRSel
RA
MPBSel
AuSPo
TRVal
AuRegR
MSPo
MPTime
IoError
RCPY
Param
AuRegSel
AuPosVal
LimLO
MV
LimHO
MPReal
EnRcpy
IoSimuW
LimHSPStLimLSPSt
StsReg01
AuPosVSt
FoMoStRegSt
MVSt
IoErrorW
AuMoSt
RegSelSt
TRSt
ScalingSt
AuSPoSt
OutOD
ParamSt
SPoSt
MMoSt
LimLOSt
OutO
LimHOSt
PosValSt
FBI_0
MultiController1
s0
s2
t1t2
r2
t6
r5
s3
s5
s10
r4
s8
start
s11
SetPoint
s1
r1
s6
s4
r3
t0
t5
r0
r6
t4
s9
MV
t3
s7
Output
FBI_1
RST_sc2
Ny
Tref
start
d
Te
MV
H
SetPointOUT
Kraidzbh
FBI_2
PFCgene_sc3
LimLSetPoint
RangeHSetPoint
Time_constant
LimLOutput
RangeLSetPoint
Tr
LimHOutput
SetPoint
ReverseAction
Order
Delay
PI_RA
Gain
Instable
LimHSetPoint
MV
Start
Output
FBI_4
SmithPredictor_sc6
INITPVSPRCPYIMPTUNELIMMANYMAN
YIMVERR
FBI_6
SF1_V24
INITPVSPRCPYIMPTUNELIMMANYMAN
YIMV
ERREUR
FBI_5
DC3_V25
INITPVSPRCPYIMPTUNELIMDECOMPMANYMAN
YIMVERR
FBI_3
IF1_V27
PVSPFFRCPYMAN_AUTOPARATR_ITR_SOUT OUT
STATUS
MA_O
OUTD
INFO
FBI_7
PIDFF8
The MultiController is a standard UNICOS object for Schneider PLC and PVSS SCADA system
Replace UNICOS PID controller UNICOS compatible (modes,
connection, hierarchy) It has a single interface for all
regulation algorithms The design allows the addition of
new control loop algorithms without changing the object interface
It has been design to offer a recipe mechanism. It allows the process expert to keep and reuse pertinent sets of tuning parameters
IF1
PIDMultiController
RST
DC3 SF1
PFC generalized
Smith Predictor
Sébastien Cabaret - October 200723
Application: MultiController object in GCS project
The MultiController is a standard UNICOS object for Schneider PLC and PVSS SCADA system
It has a unique Human Machine Interface with different views
It is composed of a synoptic, trend views, navigation buttons
It allows a global control of the regulation loop via a centralized object representation in the HMI with different views
Sébastien Cabaret - October 200725
MultiController future application: adaptive control
System to control
Online ModelIdentification under PLC
u
y
Model representation:Ex: first order in discrete approach
B1.z-1
H(z)= 1+A1.z-1
GPC tuningMechanism in PLC(Predictive strategy)
A1, B1
GPCParameters
Set Point
EN
TR
Ramp
LimHSPLimLSP
MRegSel
Scaling
FromOutO
ManReg01
AuAuMoRMPosVal
MPTSel
IoSimu
MPRSel
RA
MPBSel
AuSPo
TRVal
AuRegR
MSPo
MPTime
IoError
RCPY
Param
AuRegSel
AuPosVal
LimLO
MV
LimHO
MPReal
EnRcpy
ENO
IoSimuW
LimHSPStLimLSPSt
StsReg01
AuPosVSt
FoMoStRegSt
MVSt
IoErrorW
AuMoSt
RegSelSt
TRSt
ScalingSt
AuSPoSt
OutOD
ParamSt
SPoSt
MMoSt
LimLOSt
OutO
LimHOSt
PosValSt
FBI_1
MultiController14
MultiController