| The inertial stabilized platform system plays an important role in the imaging system of multi-rotor UAV,because it can effectively isolate the angular motion and vibration of the base.At the same time,different from other applications of inertial stabilized platforms,multi-rotor UAV has a large rotation motion range in the working process,which brings different low-frequency disturbance to various sensors mounted on the UAV.The motion coupling from the base will greatly affect the stability accuracy of the system.Moreover,the frequent acceleration and deceleration of MUAV will bring uncontrollable interference to the inertial sensors used in the inertial stabilized platform.Therefore,the following research work was carried out in this paper for the multi-rotor UAV airborne three-axis inertial platform:(1)The mathematical model of the three-axis inertial stable platform frame was established,the problem of inertia coupling was fully considered,and the conditions for reducing the inertia coupling are given.The dynamic simulation of frame system under the condition of multi-axis base disturbance was carried out.The results show that the coupling between pitch frame and course frame was more serious than that between pitch frame and roll frame under the interference of multi-axis motion of the base,which provides a certain theoretical basis for the stability control of inertial stabilized platform.(2)The gyroscope,accelerometer and magnetometer in THE MEMS inertial measurement unit mounted on the MUAV inertial stabilized platform were tested and corrected,and the correspondence between quaternion and Euler Angle in rigid body rotation was studied.The interference suppression of multi-source information fusion in motion state was studied.Combined with Kalman filtering theory,an attitude solution based on two-stage trackless Kalman filtering and continuous external acceleration vector estimation was proposed.The simulation results of the attitude solution of the horizontal roller show that the two-stage Kalman solution can effectively fuse the data according to the characteristics of the sensor in the static state.In the motion state,compared with the threshold switching algorithm,the continuous external acceleration vector estimation algorithm has an obvious suppression effect on the external acceleration interference,which can significantly improve the accuracy of the attitude solution system of the inertial stabilization platform.(3)A control system was designed for the inertial stable platform model.With the help of the adaptive capability of BP neural network,it was combined with the ordinary PID controller to realize the online self-tuning of PID parameters to adapt to the system changes of inertial stable platform,and a variety of base perturbations are simulated.The simulation results show that compared with the PID controller,the controller designed in this paper can effectively reduce the impact of multi-directional large disturbance on the stability performance of the inertial stable platform and improve the tracking stability accuracy of the system.(4)A object-oriented simulation program of the posture solution system and the control system of the inertial stability platform was designed by MATLAB language.In order to reduce code redundancy,various interfaces are introduced in the programming process,and the UML static structure of key classes in the program and the UML sequences of main algorithm processes are analyzed.The Kalman filter system program can choose different system objects,and the control system program can switch between the ordinary PID controller and the neural network PID controller,which improves the expandability of the program. |
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