Research On Attitude Measurement And Control Strategy Of Series-parallel Stabilized Platform

When the ship is sailing on the sea,it will be affected by sea wave,sea breeze,ocean current and other ocean disturbances so the carrier can cause swing and vibration,which leads to the optical precision instruments,weapon aiming systems,shipborne radar and communication systems on the carrier cannot work normally.With the development of the modernization of China's naval forces,the research of water surface weapons and equipment is becoming more and more important.Therefore,a problem of water surface weapon equipment urgently needed to be solved is how to overcome the carrier drag,torque vector swing,and vibration interference.The stable platform is a device which can keep the stable object under the action of the external disturbance to keep the position of the relative inertia space,or under the action of the command torque to rotate according to the given law.A series-parallel stable platform of ship is designed as the study object to carry out theoretical analysis and experimental study in this paper.The series-parallel stabilization platform is composed of two layers,the lower stratum of series-parallel stabilization platform is the parallel stable platform to overcome the carrier's attitude interference;the upper strata of series-parallel stabilization platform is the series tracking platform to track real-time targets.Based on the new series-parallel stabilized platform,the dissertation focuses on the parallel stabilization platform,hereinafter referred to as the stable platform,and for the series parallel stable platform system,studys the key technology of the influence of error sources,stable accuracy of attitude measurement,stable platform system modeling,control strategy and attitude disturbance prediction to carry out theoretical study and experimental verification.1.A new series-parallel intelligent stable platform system is designed,and it can not only overcome the interference effect caused by the disturbance of the attitude of the carrier,but also can track the target in real time.The lower stratum of series-parallel intelligent stable platform system is the parallel stable platform,the platform is directly drived by permanent magnet AC servo motor,by feedbacking the attitude measuring sensor silicon micro gyroscope for real-time measurement pitch and roll angle information of stabilized platform to the high speed DSP motion control module,to control the servo driving mechanism to adjust and form a closed loop,to overcome attitude disturbance in real-time;The lower stratum of series-parallel intelligent stable platform system is the parallel tracking platform,and by using the attitude information aiming system and inclinometer to measure the position of target and the attitude information of tracking platform,the tracking platform uses high-speed DSP motion control module to realize the rotation and pitch tracking so as to achieve the function of real-time tracking.This paper describes in detail the system composition and the overall scheme of the series parallel intelligent stabilized platform system,and the working principle and main error sources of the series parallel stabilized platform system are introduced and analyzed.2.The series-parallel stable platform system is a kind of mechanical and electrical equipment which requires high precision and strong real-time performance,based on the analysis of the structure and dynamics of the stabilized platform system,the kinematics analysis is carried out.In the stable platform system,the silicon micro gyroscope and the tilting instrument are used to measure the attitude information of the parallel stable platform and the series tracking platform.Aiming at the linear and non-linear errors in the output error of the inclinometer,the single error model compensation can not meet the system requirements,in this paper,an error multi-step compensation method based on least squares method and RBF neural network is proposed.Aiming at the influence of drift error and noise in the gyro output signal,based on the previous studies,the Singer model in the field of maneuvering tracking is optimized and the gyro signal is directly modeled,and the conventional Kalman filter method is optimized,based on the IMM model,a method of denoising MEMS gyro output signal based on MS-IMMIKF is proposed,the results show that the method can obtain the ideal effect on the signal denoising of the gyroscope.3.In order to realize the high precision control of the stable platform,the three-ring control structure of the current loop,the speed loop and the position loop is established.An interference observer and the grey predictive controller are introduced in the velocity stabilization ring,and the disturbance observer and the gray predictive controller are combined into the stable platform system.Previous studies have shown that the classical disturbance observer can better suppress the influence of low frequency disturbance in the velocity loop,but it is not ideal for the suppression of high frequency measurement noise and model perturbation.Aiming at this problem,an improved disturbance observer is introduced,and the fractional order is studied for the conventional integer order disturbance observer.The integer order low pass filter is replaced by fractional order filter,an interference suppression method based on gray predictive control and fractional order improved disturbance observer is proposed,and the adaptive adjustment module is established for the forecasting step and prediction error of gray prediction to improve the responsiveness of the system and reduce the impact of the prediction error on the output of the system,the numerical simulation results show that the control method can not only suppress the influence of friction torque and noise measurement,but also improve the response capability of the system,4.In the stable platform position tracking loop,after analyzing the time delay characteristic of the position tracking loop and the attitude disturbance of the carrier,a composite control method(CAGPC)based on adaptive gray predictive control is proposed.By introducing a gray predictive controller into the feedback channel to solve the influence of the system time delay.Aiming at the drawbacks of the prediction error of the conventional fixed-step gray prediction and prediction model,an adaptive adjustment module is proposed to adjust the prediction step and the prediction error weight of integrated error,according to the actual error and prediction error of the control system,the weights of the grey prediction step and the prediction error are adjusted to improve the adaptability of the prediction model and the control precision of the system.The feedforward compensation controller is introduced to restrain the disturbance to improve the disturbance rejection of the stabilized platform servo system.Finally,the numerical simulation and stability platform experiments show that the composite control method based on adaptive gray prediction control improves the response and interference suppression of the stable platform servo system.5.In order to advance the prediction of the carrier attitude disturbance,the advance control is realized in the feedforward channel.On the basis of the analysis of the chaotic characteristics of the ship carrier attitude disturbance sequence,a new method based on the grey-chaotic prediction for the prediction of the carrier attitude disturbance is proposed,the improved GM(1.1)grey prediction model is used to study the evolution of the L1 norm of the reconstructed phase points in the reconstructed phase space,the predicted values of the original attitude time series can be obtained by the L1 norm of the inverse solution of the L1 norm.Finally,the method are verified by numerical simulation and experiment,the results show that the design of the series parallel type intelligent stable platform system is effective and feasible.