Abstract
This paper puts forward Kalman filter algorithm to improve the accuracy and the stability of four rotor aircraft control. The algorithm principle is that making use of covariance to estimate the system optimal output.The flight and control theory of four rotor aircraft is first analysed, furthermore, it is found that the attitude angle has the biggest influence to its control. Then, the Kalman filter model is established for processing attitude angle information from gyro and accelerometer sensors. Finally, the algorithm is compared with complementary filter. The flight conditions is simulated in different flight environment, it is shown that Kalman filter algorithm can improve the precision and real time more greatly in attitude angle acquisition.
Highlights
A four rotor aircraft has advantages of simple structure and easy control as an aircraft that can hover, take-off and land vertically [9,10,11]
This paper first establishes the state equation, which describes the information acquisition process of a four rotor aircraft attitude angle, the data obtained from the accelerometer and gyroscope, respectively, as a Kalman filter, and the value of the observation and state estimation
We proved the superiority of the Kalman filter compared to other commonly used filter methods through the simulation [14,15,16]
Summary
A four rotor aircraft has advantages of simple structure and easy control as an aircraft that can hover, take-off and land vertically [9,10,11]. Owing to the problems of control precision and aircraft stability, its work environment and volume are extremely limited. Reference [2] applied a complementary filter algorithm by reducing the processor speed and accuracy requirements and achieved a small four rotor aircraft attitude signal solution. References [1] and [2] achieved some good effects in obtaining accurate attitude signals for four rotor aircraft. Reference [4] put forward an unscented Kalman filter to improve the filter accuracy, aiming at the error of attitude signal. This paper first establishes the state equation, which describes the information acquisition process of a four rotor aircraft attitude angle, the data obtained from the accelerometer and gyroscope, respectively, as a Kalman filter, and the value of the observation and state estimation. We proved the superiority of the Kalman filter compared to other commonly used filter methods through the simulation [14,15,16]
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