Estimation of state vector for unmanned aerial vehicle (UAV) subject to non-linear characteristics of control object
Аuthors1*, **, 2***
2. Main research and testing center for robotics Ministry of Defense of the Russian , 5, ul. Seregina, Moscow, 125167, Russia
In this article we consider new method for obtaining estimation of state vector for unmanned aerial vehicle (UAV) with use of identifier based on prediction operation from optimal Kalman filter. Estimation of non-observable UAV coordinates is being performed. Such coordinates are: flight-path angle, sideslip angle, vertical and horizontal wind angles. In order to exclude variable coefficients from equation for decreasing computation complexity we suggest to freeze coefficients which are most valuable for estimations of coordinates of Kalman gain matrix and set to zero its rest coefficients. Because of non-linear characteristics of elevator, rudder and aileron actuators we should take into consideration velocity and position constraints of these control surfaces. In this article we suggest the method which allows us to take these constraints in consideration. Also we present simulations of UAV landing and obtained results.
Keywords:Kalman filter, identifier, wind, landing, glide-path tracking.
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