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, where the open loop model generates current state derivatives, solver state errors, and 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 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. 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 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, where the open loop model generates current state derivatives, solver state errors, and 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 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, 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: A system for simulating an operation of a gas turbine engine is disclosed, having a computing system and a FADEC in electronic communication therewith, the computer system simulating an engine state. In each delta time, being the FADEC sampling rate (1) the FADEC: senses the simulated engine state from the computing system; determines a difference between the sensed state and a predetermined engine state; and outputs engine control commands intended for achieving the predetermined state; and (2) the computing system: receives the FADEC output; utilizes the output in an m×m Jacobian Block, having m active balances; and performs a reduced balance simulation, wherein: fewer than m columns of the Block are analyzed, the analysis of each column defining a Rolling Jacobian Pass; output from the Rolling Jacobian Passes is integrated into the Block, to define an updated simulated engine state; and the updated state is communicated to the FADEC.

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. 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.