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Kraft PulpingModeling& Control

Control of Continuous Kraft Digesters

Professor Richard GustafsonProfessor Richard Gustafson

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Kraft PulpingModeling& Control

Continuous Digester ControlBasics

• 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

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Kraft PulpingModeling& Control

Continuous Digester ControlBasics

• 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.

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Kraft PulpingModeling& Control

Continuous Digester ControlAdvanced 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.

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Kraft PulpingModeling& Control

MPC - SCA-NordlinerMichaelsen 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.

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Kraft PulpingModeling& Control

MPC - SCA-NordlinerControl Strategy

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Kraft PulpingModeling& Control

MPC - SCA-NordlinerReal time model with estimator

• Standard deviation of error between 3 and 4.• Standard deviation of error between 3 and 4.

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Kraft PulpingModeling& Control

MPC - SCA-NordlinerSimulated 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

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Kraft PulpingModeling& Control

Model Predictive ControlDoyle 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.

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Kraft PulpingModeling& Control

MPC -Doyle and KayihanControl 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.

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Kraft PulpingModeling& Control

MPC -Doyle and KayihanDisturbance 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

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Kraft PulpingModeling& Control

MPC -Doyle and KayihanControl 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.

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Kraft PulpingModeling& Control

MPC -Doyle and KayihanSimulated 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 Feedback MPC with all controlled outpts