Abstract: 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 generates current state derivatives and synthesized parameters as a function of the dynamic states and the model input, wherein a constraint on the current state derivatives is based a series of modules, each member of the series of modules arranged in at least a primary stream group and a secondary stream group corresponding to a component of the system. The model processor may further include an estimate state module for determining an estimated state of the model.

Abstract: 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 determining estimator gain associated with the current state model and applying the estimator gain to determine the estimated state of the model.

Abstract: Systems and methods for controlling a fluid based 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, the dynamic states input to an open loop model based on the model operating mode, wherein the open loop model generates current state derivatives, solver state errors, synthesized parameters as a function of the dynamic states and a model input vector. A constraint on the state derivatives and solver state errors is based on a series, of utilities that are based on mathematical abstractions of physical laws that govern behavior of the component. The model processor may include an estimate state module for determining an estimated state of the model based on at least one of a prior state, the current state derivatives, the solver state errors, and the synthesized parameters.

Abstract: 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, 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 a series of cycle synthesis modules, each member of the series of cycle synthesis modules modeling a component of a cycle of the control system and including a series of utilities, the utilities are based on mathematical abstractions of physical properties associated with the component.

Abstract: Systems and methods for controlling a fluid based engineering system are disclosed. The systems and methods may include a model processor configured to generate 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 a model operating mode. The model processor may further include an estimate state module configured to determine an estimated state of the model based on at least one of a prior state, current state derivatives, solver state errors, and synthesized parameters, the estimate state module using online linearization and gain calculation to determine estimator gain for determining the estimated state of the model.

Abstract: 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.

Abstract: A gas turbine engine comprises a compressor, a combustor, a turbine, and an electronic engine control system. The compressor, combustor, and turbine are arranged in flow series. The electronic engine control system is configured to generate a real-time estimate of compressor stall margin from an engine model, and command engine actuators to correct for the difference between the real time estimate of compressor stall margin and a required stall margin.

Abstract: 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 include an input object for processing model input and setting a model operating mode, the model operating mode being a starting mode if the model input is within a data range associated with a starting operation of the control device. 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.

Abstract: 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, 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 a series of cycle synthesis modules, each member of the series of cycle synthesis modules modeling a component of a cycle of the control system and including a series of utilities, the utilities are based on mathematical abstractions of physical properties associated with the component.

Abstract: 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 system may include a control law for directing the actuator as a function of a model output and for determining if the control device is operating with deteriorated conditions. 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 an open loop model.

Abstract: 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, 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 a series of cycle synthesis modules, each member of the series of cycle synthesis modules modeling a component of a cycle of the control system and including a series of utilities, the utilities are based on mathematical abstractions of physical properties associated with the component.

Abstract: 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, 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 a series of cycle synthesis modules, each member of the series of cycle synthesis modules modeling a component of a cycle of the control system and including a series of utilities, the utilities are based on mathematical abstractions of physical properties associated with the component. 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.

Abstract: 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, 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 a series of cycle synthesis modules, each member of the series of cycle synthesis modules modeling a component of a cycle of the control system and including a series of utilities, the utilities are based on mathematical abstractions of physical properties associated with the component. 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.

Abstract: 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, 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 a series of cycle synthesis modules, each member of the series of cycle synthesis modules modeling a component of a cycle of the control system and including a series of utilities, the utilities are based on mathematical abstractions of physical properties associated with the component, the series of cycle synthesis modules including a rotary apparatus module which estimates a tip clearance between the rotor and the rotor case.

Abstract: 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 determining estimator gain associated with the current state model and applying the estimator gain to determine the estimated state of the model.

Abstract: 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.

Abstract: A gas turbine engine inlet sensor fault detection and accommodation system comprises an engine model, an engine parameter comparison block, an inlet condition estimator, control laws, and a fault detection and accommodation system. The engine model is configured to produce a real-time model-based estimate of engine parameters. The engine parameter comparison block is configured to produce residuals indicating the difference between the real-time model-based estimate of engine parameters and sensed values of the engine parameters. The inlet condition estimator is configured to iteratively adjust an estimate of inlet conditions based on the residuals. The control laws are configured to produce engine control parameters for control of gas turbine engine actuators based on the inlet conditions.

Abstract: A gas turbine engine inlet sensor fault detection and accommodation system comprises an engine model, an engine parameter comparison block, an inlet condition estimator, control laws, and a fault detection and accommodation system. The engine model is configured to produce a real-time model-based estimate of engine parameters. The engine parameter comparison block is configured to produce residuals indicating the difference between the real-time model-based estimate of engine parameters and sensed values of the engine parameters. The inlet condition estimator is configured to iteratively adjust an estimate of inlet conditions based on the residuals. The control laws are configured to produce engine control parameters for control of gas turbine engine actuators based on the inlet conditions.

Abstract: A gas turbine engine comprises a compressor, a combustor, a turbine, and an electronic engine control system. The compressor, combustor, and turbine are arranged in flow series. The electronic engine control system is configured to generate a real-time estimate of compressor stall margin from an engine model, and command engine actuators to correct for the difference between the real time estimate of compressor stall margin and a required stall margin.

Abstract: A system comprises an apparatus, an actuator and a processor. The apparatus defines a flow path through an aperture, the aperture defines a pressure drop along the flow path, and the actuator regulates fluid flow across the pressure drop. The processor comprises a flow module, a comparator, an estimator and a control law. The flow module maps a flow curve relating a flow parameter to a pressure ratio, and defines a solution point located on the flow curve and a focus point located off the flow curve. The comparator generates an error as a function of a slope defined between the focus and solution points. The estimator moves the solution point along the flow curve, such that the error is minimized. The control law directs the actuator to position the control element, such that the flow parameter describes the fluid flow and the pressure ratio describes the pressure drop.