Position Servo Control Of Photoelectric Tracking System

The photoelectric tracking system has the functions of capturing and tracking targets.It has been widely used in various fields of national defense and national economy such as rocket launch test,shooting range test,fire control system for tactical support,laser tracking measurement system for large workpieces,and forest fire protection system.In view of the problems of slow response speed and low tracking accuracy in the position servo control of photoelectric tracking,this paper takes the photoelectric tracking system as the background and the vector control technology as the basis.It combines intelligent control technology with PID control to control the PMSM to make the photoelectric tracking system quickly and accurately captures and tracks the target,and after Matlab/Simulink simulation,the effectiveness of the control method is verified.First of all,mathematical model for PMSM is set up,and determined to use_di=0 vector control,and the three-loop control structure of position,speed,and electric current,then used PID controller for control simulation.Secondly,the network structure of RBF neural network,the learning process,and the principle of RBFNN-PID control are introduced.The topology of RBF neural network is simple and the nonlinear approximation ability is strong.Used RBFNN's Jacobian information to judge the control sensitivity of the system,and generate the adjustment amount of the k_p?_ik?k_d in the PID controller in real time to improve the adaptive ability of the control system.However,due to the problems of slow convergence and poor robustness in the RBFNN-PID control process,the ant colony algorithm is introduced to select RBFNN network parameters,which is a evolutionary algorithm with enhanced learning and global optimization ability.And used improved adaptive chaotic ant colony algorithm to prevent the ant colony algorithm from falling into local optimum,quickly select the optimal network to adjust PID parameters in real time,enhance the adaptive ability of the system control and anti-interference ability,improve the speed and control accuracy of the system.Finally,through Matlab/Simulink theoretical simulation and laboratory experiments have initially verified the feasibility and effectiveness of the program.