Abstract: Systems and methods for controlling a fluid-based system are disclosed. The systems and methods may include generating a model output using a model processor, processing a model input vector and setting a model operating mode, and setting dynamic states of the model processor, the dynamic states input to an open loop model based on the model operating mode. Synthesized parameters are generated as a function of the dynamic states and the model input vector based on a series of utilities, where at least one of the utilities is a configurable utility including one or more sub-utilities. An estimated state of the model is determined based on at least one of a prior state and the synthesized parameters. An actuator associated with the control device is directed as a function of a model output, where the model output includes an estimated thrust value for the control device.

Abstract: Systems and methods for controlling a fluid-based system are disclosed. The systems and methods may include generating a model output using a model processor, processing a model input vector and setting a model operating mode, and setting dynamic states of the model processor, the dynamic states input to an open loop model based on the model operating mode. Synthesized parameters are generated as a function of the dynamic states and the model input vector based on a series of utilities, where at least one of the utilities is a configurable utility including one or more sub-utilities. An estimated state of the model is determined based on at least one of a prior state and the synthesized parameters. An actuator associated with the control device is directed as a function of a model output, where the model output includes an estimated thrust value for the control device.

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 current state derivatives and solver state errors is based on mathematical abstractions of physical laws that govern behavior of a component of a cycle of a control device. The model processor may further 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 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 current state derivatives and solver state errors is based on mathematical abstractions of physical laws that govern behavior of a component of a cycle of a control device. The model processor may further 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 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. 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.