1. Kraft Pulping Modeling & Control 1 Control of Continuous Kraft Digesters Professor Richard Gustafson

2. Kraft Pulping Modeling & Control 2 Continuous Digester Control Basics Controlled Variables »Outlet kappa »EA in various sections of digester »Chip level Manipulated Variables »Lower heater temperature »White liquor charge »Chip flowrate Controlled Variables »Outlet kappa »EA in various sections of digester »Chip level Manipulated Variables »Lower heater temperature »White liquor charge »Chip flowrate

3. Kraft Pulping Modeling & Control 3 Continuous Digester Control Basics Most mills will shoot for constant chip level and EA charge to the digester. The main manipulated variable is the lower heater outlet temperature. Blow kappa is used as feedback for control. Most mills will shoot for constant chip level and EA charge to the digester. The main manipulated variable is the lower heater outlet temperature. Blow kappa is used as feedback for control.

4. Kraft Pulping Modeling & Control 4 Continuous Digester Control Advanced Control Many research papers have been published on advanced digester control (MPC, Fuzzy-Neural, PLS, etc.). The majority are all based on model simulations with little or no real-time plant data or results. Many research papers have been published on advanced digester control (MPC, Fuzzy-Neural, PLS, etc.). The majority are all based on model simulations with little or no real-time plant data or results.

5. Kraft Pulping Modeling & Control 5 MPC - SCA-Nordliner Michaelsen et al. Control strategy uses a simplified real time non- linear dynamic model of digester based on Purdue model. State and model parameter estimator (Kalman Filter) used to update real time dynamic model. Linearized form of dynamic model along with real time model used to optimize future behavior of digester. Control strategy uses a simplified real time non- linear dynamic model of digester based on Purdue model. State and model parameter estimator (Kalman Filter) used to update real time dynamic model. Linearized form of dynamic model along with real time model used to optimize future behavior of digester.

6. Kraft Pulping Modeling & Control 6 MPC - SCA-Nordliner Control Strategy

7. Kraft Pulping Modeling & Control 7 MPC - SCA-Nordliner Real time model with estimator Standard deviation of error between 3 and 4.

8. Kraft Pulping Modeling & Control 8 MPC - SCA-Nordliner Simulated results PI control uses lower heater temperature. MPC uses lower heater temp. and alkali to top of digester PI control uses lower heater temperature. MPC uses lower heater temp. and alkali to top of digester

9. Kraft Pulping Modeling & Control 9 Model Predictive Control Doyle and Kayihan Model based control developed from fundamental model. Control model derived using bump tests on fundamental model. Control model is coupled with state and parameter estimation. Most controlled output variables are currently unavailable with current sensor technology. Model based control developed from fundamental model. Control model derived using bump tests on fundamental model. Control model is coupled with state and parameter estimation. Most controlled output variables are currently unavailable with current sensor technology.

10. Kraft Pulping Modeling & Control 10 MPC -Doyle and Kayihan Control Variables Controlled Variables »Final kappa, mcc kappa, emcc kappa, upper and lower residual EA Manipulated Variables »Upper extraction flowrate, temperatures of cook, emc, and emcc heaters, mcc trim white liquor flow rate. Controlled Variables »Final kappa, mcc kappa, emcc kappa, upper and lower residual EA Manipulated Variables »Upper extraction flowrate, temperatures of cook, emc, and emcc heaters, mcc trim white liquor flow rate.

11. Kraft Pulping Modeling & Control 11 MPC -Doyle and Kayihan Disturbance Variables Measured »Chip flowrate, chip moisture, white liquor EA Unmeasured »Chip lignin content Measured »Chip flowrate, chip moisture, white liquor EA Unmeasured »Chip lignin content

12. Kraft Pulping Modeling & Control 12 MPC -Doyle and Kayihan Control Objectives Minimize final kappa variations. Control profile of kappa and cooking chemicals through digester. Minimize final kappa variations. Control profile of kappa and cooking chemicals through digester.

13. Kraft Pulping Modeling & Control 13 MPC -Doyle and Kayihan Simulated Results Both conventional and advanced control final kappa well. Advanced provides better kappa profile in digester. Both conventional and advanced control final kappa well. Advanced provides better kappa profile in digester. PI FeedbackMPC with all controlled outpts