Compact aero-thermo model real time linearization based state estimator

US9915206B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-9915206-B2
Application numberUS-201414765672-A
CountryUS
Kind codeB2
Filing dateMar 14, 2014
Priority dateMar 15, 2013
Publication dateMar 13, 2018
Grant dateMar 13, 2018

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Abstract

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Systems and methods for controlling a fluid based engineering system are disclosed. The systems and methods may include a model processor for generating a model output, the model processor including a set state module for setting dynamic states of the model processor, the dynamic states input to an open loop model based on the model operating mode. The model processor may further include an estimate state module for determining an estimated state of the model based on a prior state model output and the current state model of the open loop model the estimate state module using online linearization and gain calculation to determine estimator gain for determining the estimated state of the model.

First claim

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What is claimed is: 1. A control system, comprising: an actuator for positioning a control device comprising a control surface, wherein the actuator positions the control surface in order to control a model state; a control law for directing the actuator as a function of a model output; and a model processor for generating the model output, the model processor comprising: an input object for processing model input and setting a model operating mode; a set state module for setting dynamic states of the model processor, the dynamic states input to an open loop model based on the model operating mode; wherein the open loop model generates a current state model as a function of the dynamic states and the model input, wherein a constraint on the current state model is based on a series of cycle synthesis modules, each member of the series of cycle synthesis modules modeling a component of a cycle of the control device and comprising a series of utilities, the utilities based on mathematical abstractions of physical properties associated with the component; an estimate state module for determining an estimated state of the model based on a prior state model output and the current state model of the open loop model, the estimate state module using online linearization and gain calculation to determine estimator gain for determining the estimated state of the model; and an output object for processing the estimated state of the model to determine the model output. 2. The control system of claim 1 , wherein online linearization and gain calculation comprises obtaining partial derivatives based on the current state model. 3. The control system of claim 2 , wherein the partial derivatives based on the current state model are a Jacobian matrix. 4. The control system of claim 2 , wherein online linearization and gain calculation further comprises constructing a linear system for gain design using the partial derivatives based on the current state model. 5. The control system of claim 4 , wherein online linearization and gain calculation further comprises determining the estimator gain based on the linear system for gain design. 6. The control system of claim 1 , wherein the estimator gain is used in minimizing error vectors of the current state model. 7. The control system of claim 6 , wherein the estimate state model uses numerical integration to determine the estimated state of the model based on a prior state and a current state derivative. 8. The control system of claim 1 , wherein the control device is a gas turbine engine. 9. The control system of claim 8 , wherein the one or more cycle synthesis modules are based on one or more mathematical abstractions of physical processes associated with components of a thermodynamic cycle of the gas turbine engine. 10. A method for controlling a control device, the method comprising: generating a model output using a model processor, the model processor comprising: an input object for processing model input and setting a model operating mode; a set state module for setting dynamic states of the model processor, the dynamic states input to an open loop model based on the model operating mode; wherein the open loop model generates a current state model as a function of the dynamic states and the model input, wherein a constraint on the current state model is based on a series of cycle synthesis modules, each member of the series of cycle synthesis modules modeling a component of a cycle of the control device and comprising a series of utilities, the utilities based on mathematical abstractions of physical properties associated with the component; an estimate state module for determining an estimated state of the model based on a prior state model output and the current state model of the open loop model the estimate state module using online linearization and gain calculation to determine estimator gain for determining the estimated state of the model; and an output object for processing the estimated state of the model to determine a model output; directing an actuator associated with the control device as a function of the model output using a control law; and positioning the control device comprising a control surface using the actuator, wherein the actuator positions the control surface in order to control the model state. 11. The method of claim 10 , wherein online linearization and gain calculation comprises obtaining partial derivatives based on the current state model. 12. The method of claim 11 , wherein online linearization and gain calculation further comprises constructing a linear system for gain design using the partial derivatives based on the current state model. 13. The method of claim 12 , wherein online linearization and gain calculation further comprises determining the estimator gain based on the linear system for gain design. 14. The method of claim 10 , wherein the estimator gain is used in minimizing error vectors of the current state model. 15. The method of claim 14 , wherein the estimate state model uses numerical integration to determine the estimated state of the model based on a prior state and a current state derivative. 16. A gas turbine engine comprising: a fan; a compressor section downstream of the fan; a combustor section downstream of the compressor section; a turbine section downstream of the combustor section; an actuator for positioning the gas turbine engine, wherein the actuator positions a control surface of an element of the gas turbine engine in order to control a model state; a control law for directing the actuator as a function of a model output; a model processor for generating the model output, the model processor comprising: an input object for processing model input and setting a model operating mode; a set state module for setting dynamic states of the model processor, the dynamic states input to an open loop model based on the model operating mode; wherein the open loop model generates a current state model as a function of the dynamic states and the model input, wherein a constraint on the current state model is based on a series of cycle synthesis modules, each member of the series of cycle synthesis modules modeling a component of a cycle of the gas turbine engine and comprising a series of utilities, the utilities based on mathematical abstractions of physical properties associated with the component; an estimate state module for determining an estimated state of the model based on a prior state model output and the current state model of the open loop model the estimate state module using online linearization and gain calculation to determine estimator gain for determining the estimated state of the model; and an output object for processing the estimated state of the model to determine the model output. 17. The gas turbine engine of claim 16 , wherein online linearization and gain calculation comprises obtaining partial derivatives based on the current state model. 18. The gas turbine engine of claim 17 , wherein online linearization and gain calculation further comprises constructing a linear system for gain design using the partial derivatives based on the current state model. 19. The gas turbine engine of claim 18 , wherein online linearization and gain calculation further comprises determining the estimator gain based on the linear system for gain design. 20. The gas turbine engine of claim 16 , wherein the estimator gain is used in minimizing error vectors of the current state model.

Assignees

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Classifications

  • Combustors or associated equipment · CPC title

  • characterised by the type of regulator means · CPC title

  • for axial flow compressors · CPC title

  • for axial flow fans (blade mountings F04D29/34, blades F04D29/38) · CPC title

  • having a turbine driving a compressor (power transmission arrangements F02C7/36; control of working fluid flow F02C9/16) · CPC title

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What does patent US9915206B2 cover?
Systems and methods for controlling a fluid based engineering system are disclosed. The systems and methods may include a model processor for generating a model output, the model processor including a set state module for setting dynamic states of the model processor, the dynamic states input to an open loop model based on the model operating mode. The model processor may further include an est…
Who is the assignee on this patent?
United Technologies Corp
What technology area does this patent fall under?
Primary CPC classification F02C7/26. Mapped technology areas include Mechanical Engineering.
When was this patent published?
Publication date Tue Mar 13 2018 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 12 related publications on this page (citations in our corpus or others sharing the same primary CPC).