Rockwell Automation Technologies Incorporated

Rockwell Automation, Inc.

Pavilion Technologies, Inc.

Maina A Macharia

Michael Edward Tay

Patrick David Noll

James F Bartee

Donald Melvin Maxwell

Brian Kent Stephenson

Bijan Sayyar-Rodsari

Celso Axelrud

Srinivas Budaraju

Zhaozhi Wei

Patrick D Noll

System and method for determining total inventory of batch and continuous biomass inventories in a biofuel production process. Measured biomass inventory values are received, including batch inventories from multiple batch fermenters and at least one continuous beer well inventory. The values are premised on a controlled vapor pressure of the batch fermenters and beer well(s), where the pressure fluctuates in an uncontrolled manner. A measured vapor pressure for the batch fermenters and beerwell(s) is received, and pressure compensated inventory values determined based on the measured inventory and pressure values. Measured biomass input flow to the batch fermenters and output flow from the beerwell(s) are received, and are premised on a constant biomass temperature and density, where biomass temperature and density fluctuate in an uncontrolled manner. The total inventory of batch and continuous inventories is determined based on the measured flows and the pressure compensated inventory values, and stored.

Determining total inventory of batch and continuous inventories in a biofuel production process

The present invention provides novel techniques for controlling the blending of multiple fluids. In particular, the present techniques are presented in the context of biofuel production, wherein blending of a denaturant with an undenatured biofuel may be controlled and optimized. However, the present techniques may also be applied to any other suitable applications, such as the production of petroleum products, where multiple fluids may be blended.

Model predictive control of biofuel denaturant blending

The present invention provides novel techniques for controlling batch reaction processes. In particular, a parametric hybrid model may be used to parameterize inputs and outputs of batch reaction processes. The parametric hybrid model may include an empirical model, a parameter model, and a dynamic model. Critical quality parameters, which are correlated with, but not the same as, end-of-batch quality values for the batch reaction processes may be monitored during cycles of the batch reaction processes. The quality parameters may be used to generate desired batch trajectories, which may be used to control the batch reaction processes during the cycles of the batch reaction processes.

Nonlinear model predictive control of a batch reaction system

The present invention provides novel techniques for controlling the output of a distillation sub-process by controlling, using model predictive control, the temperature of steam used in the distillation sub-process, wherein the steam is generated in a milling and cooking sub-process. In particular, the present techniques are presented in the context of biofuel production, wherein the temperature of a cook tube generated in a milling and cooking sub-process may be controlled to optimize the energy utilization in the ethanol/water separation of a side stripper column, which uses the cook flash steam as an energy source. However, the present techniques may also be applied to other suitable applications, such as liquor processing, where steam generated in a different process may be used in a distillation process to help separate water from the liquor.

Cook flash temperature optimization

The present invention provides novel techniques for controlling the balance between energy usage and biofuels dehydration between a distillation process unit and molecular sieves with model predictive control technology. In particular, the present techniques are presented in the context of biofuel production, wherein control of the balance between energy usage and water removal in biofuel production may be optimized. However, the present techniques may also be applied to any other suitable applications, such as liquor processing, where energy may be used to remove water from the liquor.

Energy optimizer for dehydrating biofuels through distillation towers and molecular sieves

The present invention provides novel techniques for optimizing throughput and yield using model predictive control techniques. In particular, the present techniques are presented in the context of biofuel production, wherein the trade off between yields of biofuel production and overall system throughput may be optimized. However, the present techniques may also be applied to any other suitable applications where a batch process of the system may affect a change in a property of the produced product, such as liquor processing.

Throughput/yield optimized model predictive control

System and method for managing fermentation feed in a biofuel production process, comprising a dynamic multivariate predictive model-based controller coupled to a dynamic multivariate predictive model. The model is executable to: receive process information, including water inventory and biomass information, from the biofuel production process; receive a specified objective for the fermentation feed specifying a target biomass concentration; and generate model output comprising target values for a plurality of manipulated variables of the biofuel production process, including target flow rates of water and/or biomass contributing to the fermentation feed in accordance with the specified objective. The controller is operable to dynamically control the biofuel production process by adjusting the plurality of manipulated variables to model-determined target values to stabilize water/biomass balance in the fermentation feed in accordance with the specified objective, including the specified target biomass concentration.

Model predictive control of a fermentation feed in biofuel production

System and method for managing batch fermentation in biofuel production. An optimizer executes a nonlinear multivariate predictive model of a batch fermentation process in accordance with an end of batch objective specifying a target end of batch biofuel concentration to determine an optimal batch trajectory over a temporal control horizon specifying a biofuel and/or sugar concentration trajectory over the batch fermentation process. A nonlinear control model for the batch fermentation process that includes the temporal control horizon driven by biofuel concentration during the batch fermentation process is executed per the determined optimal batch trajectory using received process information as input, thereby generating model output including target values for manipulated variables for the batch fermentation process, including batch fermentation temperature. The batch fermentation process is controlled per the target values to produce biofuel in accordance with the determined optimal batch trajectory, to substantially optimize the end of batch biofuel yield.

Model predictive control of fermentation in biofuel production

A system and method are provided 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.

Nonlinear model predictive control of a biofuel fermentation process

A system and method are provided for integrated management of a biofuel distillation process and a biofuel dehydration process of a biofuel production process, comprising a dynamic multivariate model-based controller coupled to a dynamic multivariate predictive model. The model is executable to: receive distillation and dehydration process information including biofuel compositions, receive an objective for biofuel production output from the distillation and dehydration processes, e.g., target product composition, production rate, and/or feed rate, and generate model output comprising target values for a plurality of manipulated variables related to the distillation and dehydration processes in accordance with the objective. The controller is operable to dynamically control the biofuel production process by adjusting the plurality of manipulated variables to the model-determined target values in accordance with the objective for biofuel production.

Integrated model predictive control of distillation and dehydration sub-processes in a biofuel production process

The present invention provides novel techniques for controlling flow rates through parallel distribution paths of centrifuges and dryers using model predictive control. In particular, the present techniques are presented in the context of biofuel production, wherein control of whole stillage flow rates through parallel distribution paths of centrifuges and dryers may be optimized. However, the present techniques may also be applied to other suitable applications, such as the production of agricultural products, where parallel distribution paths of centrifuges and dryers may be used to separate solids from liquids as well as to remove water from the solids and liquids.

Optimizing product drying through parallel lines of centrifuges and dryer process units

System and method for managing a biofuel production process. An integrated dynamic multivariate predictive model is provided that includes a continuous process model representing a continuous process of the biofuel production process, a batch process model representing a batch process of the biofuel production process, and a continuous simulation framework. The batch process model interacts with the continuous process model as a nonlinear continuous process via the framework using bridging equations. An objective is received, as is constraint information specifying constraints for the biofuel production process, where the constraints are in terms of the framework, and process information related to the batch and continuous processes. The integrated model is executed per the objective using the process information as input, generating target values for variables related to the batch and continuous processes per the objective and subject to the constraints, and used to control the batch and continuous processes substantially optimally.

Integrated model predictive control of batch and continuous processes in a biofuel production process

System and method for determining total mill flow (TMF) in a biofuel production process. Measured slurry flow and density values from a process fed by mill(s), backset, and at least one water source, are received. The slurry includes biomass solids and water. Measured backset flow and density values, and a backset composition value are received, as well as a slurry composition value indicating % biomass solids of the slurry is received. A quantity of biomass solids and/or water of the slurry determined based on the slurry flow, density, and composition, and a quantity of the biomass solids and/or water of the backset determined based on the backset flow and density, backset composition, and a system filter characterizing time delays and lags between measurements of the backset flow and biomass slurry flow. Total mill flow is determined based on the quantities of biomass solids and/or water of the slurry and backset.

Determining total mill flow in a biofuel production process

A system and method are provided for controlling temperature of a batch fermenter in a biofuel production process. A nonlinear predictive integrating temperature model for a batch fermentation process is provided that is a function of fermenter level. An objective for the batch fermentation process specifying a target fermenter temperature for the batch fermentation process is received, as is process information for the batch fermentation process, including fermenter level and fermenter temperature. The nonlinear predictive integrating temperature model is executed in accordance with the objective using the process information as input to determine target values for manipulated variables for controlling fermenter temperature of the batch fermentation process. The fermenter temperature for the batch fermentation process is controlled in accordance with the target values to produce biofuel in accordance with the objective, to substantially optimize the end of batch biofuel yield.

Growing community of inventors

Round Rock, TX, United States of America

Maina A Macharia