Extended Kalman Filter Based States Estimation of Unmanned Quadrotors for Altitude-Attitude Tracking Control

Anotace: In this paper, state variables estimation and Fuzzy Sliding Mode Control (FSMC) are presented in order to estimate the state variables and altitude-attitude tracking control in presence of internal and external disturbances for unmanned quadrotor. The main idea of the proposed control strategy is the development of an Extended Kalman Filter (EKF) for the observation of the states. Fuzzy logic systems are used to adapt the unknown switching-gains to eliminate the chattering phenomenon induced by Sliding Mode Control (SMC). The stability of the system is guaranteed in the sense of Lyapunov. The effectiveness and robustness of the proposed controller-observer scheme that takes into account internal and external disturbances are demonstrated on computer simulation using Matlab environment.