IJCAS

Hardware-in-the-loop (HIL) simulation is an effective technique that is used for development and testing of control systems while some of the control loop components are simulated in a proper environment and the other components are real hardware. In a conventional HIL simulation, the hardware is an electronic control unit which electronic control signals are communicated between the hardware and the software. But, HIL simulation of a mechanical component requires additional transfer systems to connect the software and hardware. The HIL simulation can achieve unstable behavior or inaccurate results due to unwanted time-delay dynamic of the transfer system. This paper presents the use of Smith predictor for time-delay compensation of transfer system in the HIL simulation of an electro-hydraulic fuel control unit (FCU) for a turbojet engine. A nonlinear auto regressive with exogenous input (NARX) neural network model is used for modeling and predicting the FCU behavior. The neural model is trained by Levenberg-Marquardt algorithm and the training and validation sets are generated using the amplitude modulated pseudo random binary sequence (APRBS). The consistency of the experimental real-time simulation and off-line simulation shows the applicability of the presented method for mitigating the effect of unwanted dynamic of the transfer system in the HIL simulation.

Keywords: Fuel control unit (FCU), hardware-in-the-loop (HIL), neural network, Smith predictor, time-delay, turbojet.