Research On Stable Tracking Control Of Three-degree-of-freedom Tracking And Pointing Platform

The three-degree-of-freedom tracking and pointing platform is a stable tracking system for specified targets.Based on photoelectric sensors,which can search ? identify target on the ground or in the air,with the help of gyro to achieve inertial space stability,according to instructions to make the azimuth,pitch and roll ring rotate each other to complete the tracking and aiming of the target.This platform is widely used in military equipment,and its tracking accuracy is an important index to evaluate the performance of the system.Considering that the working environment of the system is complex and serious external interference.Therefore,in the design of tracking platform controller,it is necessary to improve the robustness,tracking speed and accuracy of the system,etc.In this paper,the working principle of the photoelectric tracking and pointing platform and the components of the stabilization loop are analyzed.Firstly,ignoring the coupling among the rings,the corresponding transfer functions are obtained by analyzing the dynamic equations of each part,finally,the motion state space model of the system under the external disturbance is established.Secondly,considering coupling among the rings,the coordinate system is set up,the dynamic equation is deduced and simplified reasonably,lastly,a more realistic state space model for the ring frame is obtained.1.Design of tracking and pointing platform controller neglecting coupling among ringsLinear Quadratic Gaussian/Loop Transfer Recovery(LQG/LTR)controller and output-feedback H? controller are designed in the stabilization loop.Then the simulation models of the system are established separately,and the simulation results are compared.The results show that both of the two control algorithms can make the system enter the steady-state rapidly and has good steady-state performance.In contrast,simulation result of output-feedback H? control has smaller overshoot,better robust,and the design of this controller does not need to observe the state,so it is more reliable.BP neural network tuning PID controller is designed in the tracking loop and compared with classical PID control.The simulation results show that the dynamic and steady-state performance of the PID algorithm based on BP neural network tuning is improved obviously.On this basis,the Smith predictor is added to improve the lag of the system.The results show that after adding Smith prediction,the delay can be compensated effectively,overshoot and adjustment time can be reduced.The system not only completes the attitude tracking quickly and accurately but also the tracking error is(27)mrade 2.0,which meets the tracking accuracy requirements.2.Design of tracking and pointing platform controller considering coupling among ringsThe design of the LQG/LTR controller is designed in the stabilization loop,and the simulation model is built to complete the verification.The simulation results show that the system not only can quickly enter the steady-state,but also has good stability and robustness.The PID controller and integral-separation PID controller are designed in the tracking loop.Adding the Smith predictor,and completes the comparative simulation of the double closed loop control system.The simulation results show that the closed-loop system can achieve fast and stable tracking.In contrast,integralseparation PID control has better dynamic and steady-state effect.