Transcript Slide 1
From regulation basics to advanced control 1 Sébastien Cabaret - October 2007 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 2 Sébastien Cabaret - October 2007 Regulation: what is a control loop? “I want to see a measured value which corresponds to my request” 3 Sébastien Cabaret - October 2007 Regulation: what is a control loop? Controller or human! Desired Temperature (ex: 150C) Acts on heating power (4-20mA) (0-500W) Reaction: The water temperature reacts on heating power changes 4 TE Sébastien Cabaret - October 2007 Temperature Sensor Regulation: what is a control loop? Control Loop system Representation Example: Open Loop representation 5 Sébastien Cabaret - October 2007 Regulation: what is a control loop? Control Loop system Representation Example: Closed Loop representation 6 Sébastien Cabaret - October 2007 G(p) C(p) Desired Temperature (SP, 150C) Acts on heating power (u, 4-20mA) Reaction: The water temperature reacts on heating power changes 7 TE Sébastien Cabaret - October 2007 Temperature Sensor (y) 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: 8 Sébastien Cabaret - October 2007 What is a PID controller? PID Elementary actions Proportional C (p ) K P 9 Sébastien Cabaret - October 2007 What is a PID controller? PID Elementary actions Integrative C I ( p) 1 Ti . p Ti is the coefficient given to increase or decrease the integrative action 10 Sébastien Cabaret - October 2007 What is a PID controller? PID Elementary actions Derivative CD ( p) Td . p Td is the coefficient given to increase or decrease the derivative action 11 Sébastien Cabaret - October 2007 What is a PID controller? PID Elementary actions Sum up 12 Sébastien Cabaret - October 2007 What is advanced control? Advanced Control System complexity Basic corrections PID Other strategies Advanced strategies Others GPC, PFC, RST, IMC… Fuzzy, Neuronal network, … Need for process identification 13 Sébastien Cabaret - October 2007 Advanced Control - Sébastien Cabaret – 9 Feb. 2006 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 Data acquisition 14 Methods Controller parameters TUNING Ex: P,I and D for PID Identification Modeling Sébastien Cabaret - October 2007 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. 15 Sébastien Cabaret - October 2007 The predictive control is closed to human driver behavior The controller contains the model of the process to drive The driver has built a «mental picture» of its car behaviors A process model is integrated into the controller SetPoint Process Output Action He knows the efficiency of the brakes and knows the effect to his car The controller has the system knowledge and is able to calculate future action to have a desire output behavior The model allows to predict the effect of the action to the system output 16 Sébastien Cabaret - October 2007 Predictive Control 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) 17 Sébastien Cabaret - October 2007 Model Set Point Horizon Real trajectory Reference trajectory 18 Sébastien Cabaret - October 2007 Future 19 Sébastien Cabaret - October 2007 Schneider tool for Modeling and Tuning available in ITCO DataStore Optireg •Some predictive algorithms •Schneider PLC •PID 20 Sébastien Cabaret - October 2007 Application: MultiController object in GCS project FBI_1 14 MultiController EN ENO MV OutO AuSPo MVSt AuRegSel SPoSt RegSelSt MRegSel IoError IoSimu AuSPoSt ManReg01 AuPosVSt AuRegR TR IoErrorW TRVal IoSimuW Ramp AuMoSt AuPosVal MMoSt AuAuMoR FoMoSt MPosVal RegSt MSPo TRSt MPReal PosValSt MPRSel MPTime MPTSel StsReg01 MPBSel LimHSP LimLSP LimHO LimLO Param Scaling EnRcpy RCPY RA FromOutO LimHSPSt LimLSPSt LimHOSt LimLOSt ParamSt ScalingSt 21 OutOD Sébastien Cabaret - October 2007 Application: MultiController object in GCS project Smith Predictor IF1 FBI_4 FBI_3 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 22 PID FBI_7 8 PIDFF PV SP FF RCPY MAN_AUTO PARA TR_I TR_S OUT INIT PV SP RCPY IMP TUNE LIM DECOMP MAN YMAN SmithPredictor_sc 7 IF1_V2 Y IMV ERR MultiController FBI_0 MultiController MV AuSPo AuRegSel OUTD MA_O INFO STATUS MRegSel IoError IoSimu ManReg01 AuRegR TR TRVal Ramp AuPosVal AuAuMoR MPosVal MSPo MPReal MPRSel MPTime MPTSel OUT FBI_1 RST_sc MV SetPoint r0 r1 r2 r3 r4 r5 r6 s0 s1 s2 s3 s4 s5 s6 s7 s8 s9 s10 s11 t0 t1 t2 t3 t4 t5 t6 start 2 Output RST DC3 FBI_5 DC3_V2 INIT PV SP RCPY IMP TUNE LIM MAN YMAN Sébastien Cabaret - October 2007 MV SetPoint Instable Order Time_constant Gain LimHOutput LimLOutput LimHSetPoint LimLSetPoint ReverseAction RangeHSetPoint RangeLSetPoint PI_RA Tr 5 Y IMV ERREUR MPBSel LimHSP LimLSP LimHO LimLO Param Scaling EnRcpy RCPY RA FromOutO 1 OutO MVSt SPoSt RegSelSt 6 Output Delay AuSPoSt AuPosVSt IoErrorW IoSimuW AuMoSt MMoSt FoMoSt RegSt TRSt PosValSt Start FBI_2 PFCgene_sc SetPoint MV y N Te Tref H d StsReg01 LimHSPSt LimLSPSt LimHOSt LimLOSt ParamSt ScalingSt start SF1 FBI_6 OutOD SF1_V2 INIT PV SP RCPY IMP TUNE LIM MAN YMAN 4 Y IMV ERR 3 OUT Kr ai dz bh 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 23 Sébastien Cabaret - October 2007 MultiController operation under PVSS 24 Sébastien Cabaret - October 2007 MultiController future application: adaptive control Model representation: Ex: first order in discrete approach System to control B1.z-1 H(z)= Online Model Identification under PLC y 1+A1.z-1 A1, B1 u GPC tuning Mechanism in PLC (Predictive strategy) GPC Parameters Set Point 25 Sébastien Cabaret - October 2007 MultiController FBI_1 14 MultiController EN ENO MV OutO AuSPo MVSt AuRegSel SPoSt RegSelSt MRegSel IoError IoSimu AuSPoSt ManReg01 AuPosVSt AuRegR TR IoErrorW TRVal IoSimuW Ramp AuMoSt AuPosVal MMoSt AuAuMoR FoMoSt MPosVal RegSt MSPo TRSt MPReal PosValSt MPRSel MPTime MPTSel StsReg01 MPBSel LimHSP LimLSP LimHO LimLO Param Scaling EnRcpy RCPY RA FromOutO LimHSPSt LimLSPSt LimHOSt LimLOSt ParamSt ScalingSt OutOD Advanced Control Questions 26 Sébastien Cabaret - October 2007