Abstract
A model and real-time simulation of a gas turbine engine (GTE) by real-time tasks (RTT) is presented. A Kalman filter is applied to perform the state vector identification of the GTE model. The obtained algorithms are recursive and multivariable; for this reason, ANSI C libraries have been developed for (a) use of matrices and vectors, (b) dynamic memory management, (c) simulation of state-space systems, (d) approximation of systems using equations in matrix finite difference, (e) computing the mean square errors vector, and (f) state vector identification of dynamic systems through digital Kalman filter. Simulations were performed in a Single Board Computer (SBC) Raspberry Pi 2® with a real-time operating system. Execution times have been measured to justify the real-time simulation. To validate the results, multiple time plots are analyzed to verify the quality and convergence time of the mean square error obtained.
Highlights
A digital filter is a hardware or software used to reduce the noise in the data of a system, extract information, or predict and rebuild the behavior of a system [1]
A real-time implementation on a Single Board Computer (SBC) of a Kalman digital filter applied to the hybrid dynamic model of a turbofan engine is proposed
As shown in [3], a real-time task Ji is described as an executable job entity characterized by arrival and restriction times associated with an instance ji,k, where i is the task index, and k is the instance index, see [4]
Summary
A digital filter is a hardware or software used to reduce the noise in the data of a system, extract information, or predict and rebuild the behavior of a system [1]. Linear dynamic models and Kalman filtering operating in real time are widespread [8,9]. A real-time implementation on a Single Board Computer (SBC) of a Kalman digital filter applied to the hybrid dynamic model of a turbofan engine is proposed. The execution time is verified at each time instance and under the conditions of a specialized computer similar to an engine control processor This examination allows us to draw a sound conclusion whether the filter and model can be implemented in real on-board engine and aircraft systems. To our knowledge, such a strict verification is novel.
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