[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Preuß et al., 2000 - Google Patents

Modelling and predictive control of fed-batch yeast growth on industrial pilot plant scale

Preuß et al., 2000

View PDF
Document ID
10856976528023783711
Author
Preuß K
Le Lann M
Proth J
Pingaud H
Publication year
Publication venue
Chemical Engineering Journal

External Links

Snippet

This paper presents an approach for modelling and control of fed-batch yeast growth which requires extensive calculation and a small number of measurements of component concentration. The process model is based on a simplified biochemical reaction description …
Continue reading at www.academia.edu (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
    • G05B13/027—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks only
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/048—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators using a predictor
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
    • G05B13/0275—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using fuzzy logic only
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
    • G05B13/0285—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks and fuzzy logic
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0205—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system
    • G05B13/024—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system in which a parameter or coefficient is automatically adjusted to optimise the performance
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D11/00—Ratio control
    • G05D11/02—Controlling ratio of two or more flows of fluid or fluent material
    • G05D11/13—Controlling ratio of two or more flows of fluid or fluent material characterised by the use of electric means
    • G05D11/131—Controlling ratio of two or more flows of fluid or fluent material characterised by the use of electric means by measuring the values related to the quantity of the individual components
    • G05D11/132—Controlling ratio of two or more flows of fluid or fluent material characterised by the use of electric means by measuring the values related to the quantity of the individual components by controlling the flow of the individual components
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D11/00—Ratio control
    • G05D11/02—Controlling ratio of two or more flows of fluid or fluent material
    • G05D11/13—Controlling ratio of two or more flows of fluid or fluent material characterised by the use of electric means
    • G05D11/135—Controlling ratio of two or more flows of fluid or fluent material characterised by the use of electric means by sensing at least one property of the mixture
    • G05D11/138—Controlling ratio of two or more flows of fluid or fluent material characterised by the use of electric means by sensing at least one property of the mixture by sensing the concentration of the mixture, e.g. measuring pH value

Similar Documents

Publication Publication Date Title
Valentinotti et al. Optimal operation of fed-batch fermentations via adaptive control of overflow metabolite
Birol et al. A modular simulation package for fed-batch fermentation: penicillin production
Srinivasan et al. Dynamic optimization of batch processes: II. Role of measurements in handling uncertainty
US9046882B2 (en) Nonlinear model predictive control of a batch reaction system
Gnoth et al. Control of cultivation processes for recombinant protein production: a review
Chen et al. Model predictive control of nonlinear singularly perturbed systems: Application to a large-scale process network
Gadkar et al. On-line adaptation of neural networks for bioprocess control
Dewasme et al. State estimation and predictive control of fed-batch cultures of hybridoma cells
Singh et al. Model-based computer-aided framework for design of process monitoring and analysis systems
US10274975B2 (en) Method and apparatus for controlling acid concentration for pickling in cold rolling
Palma-Flores et al. Simultaneous design and nonlinear model predictive control under uncertainty: A back-off approach
Wechselberger et al. PAT method to gather bioprocess parameters in real-time using simple input variables and first principle relationships
CN117952256A (en) Renewable energy system management method, device, equipment and storage medium
Ibáñez et al. Robust control of fed-batch high-cell density cultures: a simulation-based assessment
Retamal et al. Parameter estimation of a dynamic model of Escherichia coli fed-batch cultures
Preuß et al. Modelling and predictive control of fed-batch yeast growth on industrial pilot plant scale
JP3133061B2 (en) Method and apparatus for studying volume and flow fluctuations in the control of a continuous flow process
Márquez-Vera et al. Stable fuzzy control and observer via LMIs in a fermentation process
Yamada et al. Application of fuzzy control system to coenzyme Q10 fermentation
Myers et al. Process control applications of an extended Kalman filter algorithm
Gan et al. Development of a recursive time series model for fed-batch mammalian cell culture
Hocalar et al. Model based control of minimal overflow metabolite in technical scale fed-batch yeast fermentation
Yabuki et al. Industrial experiences with product quality control in semi-batch processes
Jianlin et al. Unscented transformation based robust kalman filter and its applications in fermentation process
Gjerkes et al. Product identification in industrial batch fermentation using a variable forgetting factor