Sliding Mode Control Based Study On Line-of-sight Stabilization Control Of Optoelectronic Platform

Due to internal and external disturbances,the optoelectronic platform will cause a decrease in stability accuracy and a tracking failure during operation.It is very important to design the servo control system reasonably and improve the tracking and antidisturbance performance for the stability and accuracy of the line-of-sight.The traditional PID control technology cannot take into account all kinds of nonlinear factors,so this paper based on sliding mode control(SMC)to study the line-of-sight stabilization control for the optoelectronic platform.The research results are as follows:Firstly,the composition and operation requirements of the optoelectronic platform are analyzed,and its servo system is modeled.Disturbances affecting the line-of-sight are studied and classified for subsequent development of targeted control schemes.Secondly,for the internal disturbance suppression of model parameter perturbation,adaptive robust sliding mode control(ARSMC)is studied,which is combined with internal model control(IMC)to form an IMC-ARSMC composite controller,so as to ensure the stable and accurate tracking of the line-of-sight under the internal uncertainty.To deal with the problem of parameter perturbation under more complex working conditions,an improved adaptive rate is derived to improve the estimation accuracy of uncertain parameters.The stability of IMC-ARSMC is discussed.The simulation verifies that no matter how the input disturbance changes,the tracking and antidisturbance performance of the IMC-ARSMC based on the improved adaptive rate is better than the IMC-ARSMC with the original adaptive rate.Thirdly,for the external disturbance suppression of carrier rate disturbance,the three closed-loop control method are designed by combining adaptive fuzzy sliding mode control(AFSMC)and active disturbance rejection control(ADRC).The insensitivity of SMC to uncertain factors is used to suppress the internal disturbance of the model,and the AFSMC method is used to eliminate the sliding mode chattering,thereby further improving the accuracy and efficiency of target tracking.ADRC is used to design the system position loop to eliminate the influence of velocity disturbance on the line-ofsight,and back propagation neural network(BPNN)is used to optimize parameter tuning.The three closed-loop stability composed of AFSMC and ADRC is discussed.The simulation shows that,compared with the empirical parameter tuning method,the BPNN-based parameter tuning method can avoid the blindness of parameter tuning and improve the anti-interference ability of ADRC.In addition,the three closed-loop control method enhances the robustness while improving the system stability accuracy.Finally,for the suppression of internal parameter perturbation,friction torque and external noise interference,a multi-DOF controller combined with IMC-SMC friction compensation and linear ADRC is designed.Different control problems are assigned to different degrees of freedom to solve: According to the characteristics of the friction type in the servo system of the optoelectronic platform,radial basis function neural network(RBFNN)is introduced into the IMC-SMC composite controller.The friction torque is compensated by the local approximation characteristic of RBFNN,and the model uncertainty is eliminated by the IMC-SMC.Moreover,a multi-DOF controller with linear ADRC is introduced to observe and compensate for external noise interference,and suppress strong external interference while ensuring fast and accurate tracking.The stability of multi-DOF controllers is discussed by Lyapunov principle.The simulation illustrates the good control effect of the multi-DOF controller under mixed disturbances such as parameter perturbation,friction torque,and noise disturbance,which has important reference value for the development of practical optoelectronic platform systems.