Nonlinear Model Predictive Control of a Biofuel Fermentation Process

• US 20080167852A1
• Filed: 10/30/2007
• Published: 07/10/2008
• Est. Priority Date: 10/31/2006
• Status: Active Grant

• Current Assignee: Rockwell Automation Technologies Incorporated (Rockwell Automation, Inc.)
• Original Assignee: Rockwell Automation Technologies Incorporated (Rockwell Automation, Inc.)
• Inventors: Tay, Michael E., Noll, Patrick D., Macharia, Maina A., Bartee, James F.
• Granted Patent: US 8,571,690 B2
• Time in Patent Office: Days
• US Class Current: 703/11
• CPC Class Codes: C12M 41/12 of temperature controlling the temperature of chemical or physical processes B01J19/0013, heating or cooling apparatus for laboratory use B01L7/00
• CPC Class Codes: C12M 41/44 of volume or liquid level
• CPC Class Codes: C12M 41/46 of cellular or enzymatic activity or functionality, e.g. cell viability
• CPC Class Codes: C12M 41/48 Automatic or computerized control automatic analysis G01N35/00
• CPC Class Codes: C12M 45/09 by enzymatic treatment
• CPC Class Codes: C12P 7/06 Ethanol, i.e. non-beverage
• CPC Class Codes: G05B 13/04 involving the use of models or simulators
• CPC Class Codes: G05B 13/048 using a predictor
• CPC Class Codes: Y02E 50/10 Biofuels, e.g. bio-diesel

Abstract

System and method for managing batch fermentation in a biofuel production process. A nonlinear control model of yeast growth and fermentable sugar concentration for biofuel (e.g., fuel ethanol) production in a batch fermentation process (pure and/or fed-batch fermentation) of a biofuel production process is provided. Process information for the batch fermentation process is received, and the nonlinear control model executed using the process information as input to determine values of one or more fermentation process variables for the batch fermentation process, e.g., fermentation temperature and/or enzyme flow, for substantially maximizing yeast growth and achieving target fermentable sugar concentrations. The batch fermentation process is then controlled in accordance with the determined values for the one or more fermentation process variables to substantially maximize yeast growth and achieve target fermentable sugar concentrations, where substantially maximizing yeast growth and achieving target fermentable sugar concentrations substantially maximizes biofuel production in the batch fermentation process.

Claims

1. A method for managing a batch fermentation process in a biofuel production process, comprising:

providing a nonlinear control model of yeast growth and fermentable sugar concentration for biofuel production in a batch fermentation process of a biofuel production process;

receiving process information for the batch fermentation process;

executing the nonlinear control model of yeast growth and fermentable sugar concentration using the process information as input to determine values of one or more fermentation process variables for the batch fermentation process for substantially maximizing yeast growth and achieving target fermentable sugar concentrations; and

controlling the batch fermentation process in accordance with the determined values for the one or more fermentation process variables to substantially maximize yeast growth and achieve target fermentable sugar concentrations, wherein said substantially maximizing yeast growth and achieving target fermentable sugar concentrations substantially maximizes biofuel production in the batch fermentation process.

2. The method of claim 1, wherein the one or more fermentation process variables comprise one or more of:

fermentation temperature;

or

enzyme flow, comprising a rate of enzyme flow to the fermentation process, wherein the enzyme operates to convert starches to fermentable sugar.

3. The method of claim 1, wherein the fermentable sugar comprises one or more of:

dextrose;

maltose;

fructose;

galactose;

lactose;

or

sucrose.

4. The method of claim 1, further comprising:

specifying an objective function, wherein the object function specifies;

said substantially maximizing yeast growth; and

the target fermentable sugar concentrations;

wherein said executing the nonlinear control model of yeast growth and fermentable sugar concentration comprises;

an optimizer executing the nonlinear control model of yeast growth and fermentable sugar concentration in an iterative manner to solve the object function, thereby determining the values for the one or more fermentation process variables.

5. The method of claim 1, wherein the process information comprises one or more of:

measured attributes of the batch fermentation process;

laboratory data;

or

predicted values for unmeasured attributes of the batch fermentation process computed by one or more predictive models.

6. The method of claim 1,

wherein the nonlinear control model of yeast growth and fermentable sugar concentration comprises:

a nonlinear control model of yeast growth and fermentable sugar concentration as a function of fermentation temperature and enzyme concentration; and

a nonlinear control model of temperature and enzyme concentration as a function of fermenter cooler return temperature and enzyme flow.

7. The method of claim 6, wherein said executing the nonlinear control model of yeast growth and fermentable sugar concentration comprises:

executing the nonlinear control model of yeast growth and fermentable sugar concentration as a function of fermentation temperature and enzyme concentration using the process information as input to determine values of temperature and enzyme concentration for the batch fermentation process that substantially maximize yeast growth and achieve the target fermentable sugar concentration; and

executing the nonlinear control model of temperature and enzyme concentration using the process information as input to determine the values for fermenter cooler return temperature and enzyme flow for achieving the determined values of temperature and enzyme concentration in the batch fermentation process.

8. The method of claim 1, wherein the batch fermentation process comprises a fed-batch process.

9. The method of claim 1, wherein the batch fermentation process comprises a pure batch process.

10. The method of claim 1, further comprising:

performing said receiving process information, said executing the nonlinear control model of yeast growth and fermentable sugar concentration, and said controlling the batch fermentation process in an iterative manner to produce the biofuel in a substantially optimal manner.

11. The method of claim 1, wherein the biofuel comprises one or more of:

fuel ethanol;

butanol;

or

methanol.

12. A computer-accessible memory medium configured for managing a batch fermentation process in a biofuel production process, wherein the memory medium stores:

a nonlinear control model of yeast growth and fermentable sugar concentration for biofuel production in a batch fermentation process of a biofuel production process; and

program instructions, executable to perform;

receiving process information for the batch fermentation process;

executing the nonlinear control model of yeast growth and fermentable sugar concentration using the process information as input to determine values of one or more fermentation process variables for the batch fermentation process for substantially maximizing yeast growth and achieving target fermentable sugar concentrations; and

controlling the batch fermentation process in accordance with the determined values for the one or more fermentation process variables to substantially maximize yeast growth and achieve target fermentable sugar concentrations, wherein said substantially maximizing yeast growth and achieving target fermentable sugar concentrations substantially maximizes biofuel production in the batch fermentation process.

13. The memory medium of claim 12, wherein the one or more fermentation process variables comprise one or more of:

fermentation temperature;

or

enzyme flow, comprising a rate of enzyme flow to the fermentation process, wherein the enzyme operates to convert starches to fermentable sugar.

14. The memory medium of claim 12, wherein the fermentable sugar comprises one or more of:

dextrose;

maltose;

fructose;

galactose;

lactose;

or

sucrose.

15. The memory medium of claim 12, wherein the program instructions are further executable to perform:

receiving an objective function, wherein the object function specifies;

said substantially maximizing yeast growth; and

the target fermentable sugar concentrations;

wherein said executing the nonlinear control model of yeast growth and fermentable sugar concentration comprises;

an optimizer executing the nonlinear control model of yeast growth and fermentable sugar concentration in an iterative manner to solve the object function, thereby determining the values for the one or more fermentation process variables.

16. The memory medium of claim 12, wherein the process information comprises one or more of:

measured attributes of the batch fermentation process;

laboratory data;

or

predicted values for unmeasured attributes of the batch fermentation process computed by one or more predictive models.

17. The memory medium of claim 12,

wherein the nonlinear control model of yeast growth and fermentable sugar concentration comprises:

a nonlinear control model of yeast growth and fermentable sugar concentration as a function of fermentation temperature and enzyme concentration; and

a nonlinear control model of temperature and enzyme concentration as a function of fermenter cooler return temperature and enzyme flow.

18. The memory medium of claim 17, wherein said executing the nonlinear control model of yeast growth and fermentable sugar concentration comprises:

executing the nonlinear control model of yeast growth and fermentable sugar concentration as a function of fermentation temperature and enzyme concentration using the process information as input to determine values of temperature and enzyme concentration for the batch fermentation process that substantially maximize yeast growth and achieve the target fermentable sugar concentration; and

executing the nonlinear control model of temperature and enzyme concentration using the process information as input to determine the values for fermenter cooler return temperature and enzyme flow for achieving the determined values of temperature and enzyme concentration in the batch fermentation process.

19. The memory medium of claim 12, wherein the batch fermentation process comprises a fed-batch process.

20. The memory medium of claim 12, wherein the batch fermentation process comprises a pure batch process.

21. The memory medium of claim 12, wherein the program instructions are further executable to perform:

performing said receiving process information, said executing the nonlinear control model of yeast growth and fermentable sugar concentration, and said controlling the batch fermentation process in an iterative manner to produce the biofuel in a substantially optimal manner.

22. The memory medium of claim 12, wherein the biofuel comprises one or more of:

fuel ethanol;

butanol;

or

methanol.

23. A system for managing a batch fermentation process in a biofuel production process, comprising:

a processor; and

a memory medium coupled to the processor, wherein the memory medium stores;

a nonlinear control model of yeast growth and fermentable sugar concentration for biofuel production in a batch fermentation process of a biofuel production process; and

program instructions, executable by the processor to;

receive process information for the batch fermentation process;

execute the nonlinear control model of yeast growth and fermentable sugar concentration using the process information as input to determine values of one or more fermentation process variables for the batch fermentation process for substantially maximizing yeast growth and achieving target fermentable sugar concentrations; and

control the batch fermentation process in accordance with the determined values for the one or more fermentation process variables to substantially maximize yeast growth and achieve target fermentable sugar concentrations, wherein said substantially maximizing yeast growth and achieving target fermentable sugar concentrations substantially maximizes biofuel production in the batch fermentation process.

24. The system of claim 23, wherein the program instructions are further executable to:

receive an objective function, wherein the object function specifies;

said substantially maximizing yeast growth; and

the target fermentable sugar concentrations;

wherein said executing the nonlinear control model of yeast growth and fermentable sugar concentration comprises;

an optimizer executing the nonlinear control model of yeast growth and fermentable sugar concentration in an iterative manner to solve the object function, thereby determining the values for the one or more fermentation process variables.

25. The system of claim 23, wherein the program instructions are further executable to:

perform said receiving process information, said executing the nonlinear control model of yeast growth and fermentable sugar concentration, and said controlling the batch fermentation process in an iterative manner to produce the biofuel in a substantially optimal manner.