Research On Fractional Order System Identification And Robust Control Of Photoelectric Stabilized Sighting Platform

As an advanced equipment integrating optics,precision machinery,servo control,image acquisition and processing,the photoelectric stabilized aiming platform can effectively isolate the carrier disturbance and ensure that the visual axis of the optical detection equipment maintains a stable direction in the relative inertial space.Because it can carry photoelectric detection equipment with different functions,it is widely used in military,civil and other fields,and can realize the tasks of target reconnaissance,mapping,positioning and long-range attack.When the platform works,it will be interfered by different factors such as internal and external factors,which will affect the final imaging effect of the optical load.In serious cases,it will lead to the failure of the photoelectric detection equipment.In order to improve the performance of the control system of the photoelectric stabilization and aiming platform,this thesis establishes a fractional order model that accurately represents the actual characteristic attributes of the system,and designs the corresponding fractional order controller accordingly,so as to improve the identification accuracy of the fractional order model of the system,realize the robust control of the system,and further improve the visual axis stability accuracy of the system.The main research work is as follows:Firstly,the photoelectric stabilization and aiming platform system is analyzed,including the composition,structure and classification of the system,working mode,and the factors affecting the Los stability accuracy.The mechanism of the key components in the speed ring is analyzed,and its mathematical model is obtained.The input and output signals of the system are collected through frequency scanning and scanning experiments.Based on the fractional calculus theory and the fractional characteristic analysis of the photoelectric stabilization and aiming platform,the fractional system identification of the photoelectric stabilization and aiming platform is carried out by using the intelligent optimization algorithm.In view of the disadvantage that the parameters identified by standard particle swarm optimization(PSO)are easy to fall into local optimization,the particle swarm optimization algorithm is improved combined with differential evolution(DE).The identified fractional order model of azimuth axis velocity loop is compared with the collected time-domain output signal.It is verified that the fractional order model is closer to the actual system of photoelectric stabilization and aiming platform than the integer order model.Secondly,the fractional order robust control strategy of photoelectric stabilization and aiming platform is studied.Aiming at the problems of complex solution and difficult programming of the traditional parameter setting method of fractional order controller,a parameter setting method based on vector model is adopted for FOPI,FO[PI] controller and IOPI controller,and the stability of fractional order control system is analyzed by using the stability domain decomposition method.In view of the infinite dimensional characteristics of fractional calculus operator,the approximation effect of Oustaloup and improved Oustaloup discrete algorithm on calculus operator is analyzed,and the numerical realization of fractional order model and controller is realized.The simulation results show that the fopi and FO[PI] controllers designed based on the fractional order model are better than the integer order control system in disturbance suppression ability,dynamic response characteristics and robustness,and the FO[PI] control effect is more superior.Finally,the physical verification platform of photoelectric stabilized aiming pod is built to carry out step response experiment and torque and carrier speed disturbance suppression experiment.According to the analysis of the experimental results,the FO[PI]controller based on fractional order model can effectively improve the dynamic response and disturbance suppression ability of the platform compared with the IOPI controller based on integer order model.