Optimal Operation with Changing Active Constraint Regions using Classical Advanced Control Adriana Reyes-L´ ua, Cristina Zotic˘ a, Sigurd Skogestad ∗ Department of Chemical Engineering Norwegian University of Science and Technology (NTNU) ∗ sigurd.skogestad@ntnu.no 26 July 2018 IFAC ADCHEM 2018, Shenyang, China Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 1 / 21
Outline Introduction 1 Classical Advanced Control Structures 2 Optimal Operation using Advanced Control Structures 3 Case study: Optimal Control of a Cooler 4 Conclusions 5 Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 2 / 21
1. Control Hierarchy in a Process Plant Scheduling (weeks) Site-wide optimization (weeks) The control layer is divided into: Regulatory control Local optimization (hour) CV1 MPC or Advanced Control Supervisory control Structures Control (minutes) layer CV2 PID control Regulatory control (seconds) Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 3 / 21
1. Control Hierarchy in a Process Plant Scheduling (weeks) Site-wide optimization (weeks) The control layer is divided into: Regulatory control Local optimization (hour) Supervisory/advanced control CV1 MPC or Advanced Control Supervisory control Structures Control (minutes) layer CV2 PID control Regulatory control (seconds) Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 3 / 21
1. Control Hierarchy in a Process Plant Scheduling (weeks) Site-wide optimization (weeks) The control layer is divided into: Regulatory control ◮ stable operation Local optimization (hour) Supervisory/advanced control ◮ follows the set points from long-term CV1 MPC or economic optimisation Advanced ◮ calculates the set points for the Control Supervisory control Structures Control (minutes) layer regulatory layer CV2 PID control Regulatory control (seconds) Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 3 / 21
1.Optimal Operation Objective function J min u J = J ( u , x , d ) s.t. f ( u , x , d ) = 0 g ( u , x , d ) ≤ 0 f - model equations g - operational constraints u − degrees of freedom J opt x − states u u opt d − disturbances Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 4 / 21
1.Optimal Operation Objective function J min u J = J ( u , x , d ) s.t. f ( u , x , d ) = 0 g ( u , x , d ) ≤ 0 f - model equations g - operational constraints u − degrees of freedom J opt x − states u u opt d − disturbances Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 4 / 21
1.Optimal Operation Objective function J min u J = J ( u , x , d ) s.t. f ( u , x , d ) = 0 g ( u , x , d ) ≤ 0 f - model equations g - operational constraints u − degrees of freedom J opt x − states u u opt d − disturbances Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 4 / 21
1.Optimal Operation Objective function J min u J = J ( u , x , d ) Feasable region s.t. f ( u , x , d ) = 0 g ( u , x , d ) ≤ 0 f - model equations g - operational constraints J opt u − degrees of freedom J opt x − states u u opt u opt d − disturbances Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 4 / 21
1.Active Constraints Active Constraints variables that should optimally be kept at their limiting value Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 5 / 21
1.Active Constraints Active Constraints variables that should optimally be kept at their limiting value MV constraints 1 valves, pumps CV constraints 2 pressure,temperature 1 Manipulated Variable 2 Controlled Variable Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 5 / 21
1.Active Constraints Active Constraints variables that should optimally be kept at their limiting value always control active constraints → control structure (pairing) depends on the operating region MV constraints 1 d 2 Region 3 valves, pumps CV constraints 2 Region 1 Region 2 pressure,temperature 1 Manipulated Variable 2 Controlled Variable d 1 Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 5 / 21
1.Active Constraints Active Constraints variables that should optimally be kept at their limiting value always control active constraints → control structure (pairing) depends on the operating region disturbances may change active constraint region ( space of active constraints ) MV constraints 1 d 2 Region 3 valves, pumps CV constraints 2 Region 1 Region 2 pressure,temperature 1 Manipulated Variable 2 Controlled Variable d 1 Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 5 / 21
1.Active Constraints Active Constraints variables that should optimally be kept at their limiting value always control active constraints → control structure (pairing) depends on the operating region disturbances may change active constraint region ( space of active constraints ) how to ensure optimal operation with changing active constraint region in a systematic way? MV constraints 1 d 2 Region 3 valves, pumps CV constraints 2 Region 1 Region 2 pressure,temperature 1 Manipulated Variable 2 Controlled Variable d 1 Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 5 / 21
2.Classical Advanced Control Structures Cascade control Ratio control Decoupling Feed-forward Selectors Split range control (SRC) can handle changes in active constraints Valve position control (VPC) 1 1 Also known as Input Resetting or Mid-Ranging Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 6 / 21
2.Selectors for changes in active constraints CV C1 1 min/ CV C2 max/ 2 mid CV C3 3 Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 7 / 21
2. Split Range Control (SRC) for input constraints CV2 sp CV1 sp CV2 CV CV min C2 SRC 1 2 MV1 MV2 Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 8 / 21
2. Valve Position Controller (VPC) for input constraints CV1 sp 0.95 CV1 max CV2 sp CV CV2 C1 CV VPC min C2 1 2 MV1 MV2 Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 9 / 21
2. Two Controllers with min selector as alternative to SRC CV 1 CV1 sp C1 C2 CV1 sp + CV1 sp CV2 CV2 sp min MV1 MV2 Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 10 / 21
3.Optimal Operation using Advanced Control Structures Proposed systematic procedure Step 1 Define control objectives and priority list of constraints Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 11 / 21
3.Optimal Operation using Advanced Control Structures Proposed systematic procedure Step 1 Define control objectives and priority list of constraints Step 2 Design the control system around the nominal point → choose pairings Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 11 / 21
3.Optimal Operation using Advanced Control Structures Proposed systematic procedure Step 1 Define control objectives and priority list of constraints Step 2 Design the control system around the nominal point → choose pairings Step 3 Analyse how new constraints may become active with disturbances → new active constraint region Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 11 / 21
3.Optimal Operation using Advanced Control Structures Proposed systematic procedure Step 1 Define control objectives and priority list of constraints Step 2 Design the control system around the nominal point → choose pairings Step 3 Analyse how new constraints may become active with disturbances → new active constraint region Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 11 / 21
3.Priority List In Step 1 . If there are more CVs than MV → P1 MV inequality constraints → physical constraints 1variables that minimize the loss when kept constant in spite of disturbances Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 12 / 21
3.Priority List In Step 1 . If there are more CVs than MV → P1 MV inequality constraints → physical constraints P2 CV inequality constraints → may be given up 1variables that minimize the loss when kept constant in spite of disturbances Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 12 / 21
3.Priority List In Step 1 . If there are more CVs than MV → P1 MV inequality constraints → physical constraints P2 CV inequality constraints → may be given up P3 MV or CV equality constraints → optimal operation 1variables that minimize the loss when kept constant in spite of disturbances Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 12 / 21
3.Priority List In Step 1 . If there are more CVs than MV → P1 MV inequality constraints → physical constraints P2 CV inequality constraints → may be given up P3 MV or CV equality constraints → optimal operation P4 Desired throughput (TPM) → give up at bottleneck 1variables that minimize the loss when kept constant in spite of disturbances Reyes-L´ ua et al. (NTNU) Advanced Control Structures 26 July 2018 12 / 21
Recommend
More recommend
