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. The fault detection and accommodation system is configured to detect faults in inlet condition sensors, select sensed inlet conditions for use by the control laws in the event of no fault, and select estimated inlet conditions for use by the control laws in the event of inlet condition sensor fault.
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.