| With the development of our military industry,the requirement of military equipment performance index is higher and higher,and the sea is the main battlefield of military operations,so the carrier-borne equipment has become the main object of military development,including the carrier-borne aiming equipment.Shipborne sighting equipment control system is composed of three parts: sighting equipment position control module,sighting equipment video tracking module and general command control center.The position control module of the aiming equipment is composed of two DC brush motors,which is used to control the movement of the azimuth and pitch Angle of the shipborne aiming equipment.This thsis mainly aims at improving the accuracy and stability of the aiming equipment position control module.Due to the complex situation at sea,it is prone to a lot of interference,so in view of the accuracy and stability of the DC brushless motor,the fuzzy control related ideas are added under the traditional PID control,and the artificial colony algorithm is proposed to optimize the membership function of the fuzzy control,so that the output fuzzy domain of the membership function can output the optimal PID correction according to the ITAE index.Moreover,the fuzzy control rules are designed according to the theory domain distribution of membership function to improve the adaptive ability and accuracy of the motor.In order to solve the interference of sea breeze and sea wave,Kalman filter is added to the speed feedback to reduce the influence of external noise and interference on the system.By adding the velocity profile algorithm,the motion trajectory of the shipborne aiming equipment is run according to the trapezoidal motion trajectory,which can avoid the safety risks caused by the motor starting or frequent reversing,and further improve the stability of the motor within the PID control time combined with the extrinsic calculation method.According to the simulation results,compared with the conventional fuzzy PID control algorithm,the artificial bee swarm improved fuzzy PID algorithm can effectively reduce the speed noise.Under the conventional step signal,the proposed algorithm can suppress the overshoot,and the rise time is 0.69 s,which is 49% shorter than the conventional fuzzy PID algorithm.At the same time,with the input of velocity profile,the proposed algorithm can also have a short rise time.The simulation results show that the proposed algorithm can improve the performance of the motor to a certain extent.VC++ is used to build the upper computer interface,and STM32 is used as the lower computer to develop MCU and write software code.In the physical verification,after high and low temperature test,load test and performance test,the accuracy of the proposed algorithm in rotating speed is increased by 9% compared with the conventional PID algorithm,and the position accuracy is increased by 0.1cm on average.Under 10 N interference,the peak speed is reduced by 17% and the adjustment time is shortened by 0.44 s on average,which can improve the stability and accuracy of the motor and meet the expected requirements. |
