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