Resumen
Sensors play a significant role in flight control systems. The accuracy of the measurements of state variables affects the quality and effectiveness of flight stabilization. When designing closed-loop systems, it is desirable to use sensors of the highest class and reliability, the signals of which will be as error-free as possible. False indications lead to malfunctioning of the stabilization system, and its operation does not meet the requirements set for it. There are many types of errors?bias, white noise, hysteresis, or bias drift?which affect the measurement signals from the sensors. One of the significant problems is assessing what maximum level of sensor errors stabilization system will still operate as required. In this paper, the impact of different sensor errors on flight stabilization was presented. The research was carried out using the example of an automatic flight stabilization system using aircraft trimming surfaces in a longitudinal control channel in Hardware-in-the-Loop simulations. The model simulates various types of sensor errors during flight, while the stabilization system is implemented in hardware interfaced with a real-time computer. The results of the simulations are presented and analyzed. Their comparison indicated which sensor errors affects the flight stability the most and how the effectiveness of the stabilization system changes as error increases. The presented results show changes in flight parameters due to added sensor errors. Depending on the accuracy class of the IMU, the errors more or less disrupt the operation of the system.