Research On Parameter Optimization And Control Algorithm Of Two-dimensional Ballistic Correction Projectile Actuator

As a key component of the two-dimensional trajectory correction projectile,the correction actuator itself is also a complex high-precision position servo system.In this paper,the continuous correction valve is used as the correction actuator,and the control system design of the correction actuator and the parameter optimization research of the correction actuator are carried out.The control system design includes software and hardware design,three-loop servo digital controller design and online parameter tuning algorithm.Based on the research status of two-dimensional trajectory correction actuator and control algorithm at home and abroad,this paper designs a correction servo system composed of a controller,a brushless DC motor,and a continuous correction valve.Secondly,for the software and hardware design of the modified actuator control system,a hardware circuit design scheme of the modified actuator control system based on TMS320F28335 is proposed,and the specific implementation process of each functional module circuit is introduced in detail,including the DSP minimum system,expansion circuit,and power supply circuit.,Isolated drive circuit,signal detection circuit and overcurrent,overvoltage protection circuit,etc.Based on the hardware circuit,the main program design of the system software is explained,and the three-loop control interrupt service subroutine and the voltage and current sampling program are designed and analyzed respectively.In order to improve the accuracy of trajectory correction,a hybrid particle swarm algorithm based on differential evolution is proposed to optimize the parameters of the correction actuator,and to further improve the algorithm’s global search ability and avoid stagnation in the later iterations,the particle swarm algorithm in the hybrid algorithm is nonlinear Dynamic adaptive inertia weight strategy,and introduce a mutation mechanism.The simulation results show that the improved hybrid particle swarm algorithm based on differential evolution has higher solution accuracy,can speed up the convergence speed,can effectively avoid the problem of the algorithm falling into the local extremum in the later iteration,and has good result robustness.Finally,determine the control strategy of the three-loop servo system,and carry out parameter design and modeling.At the same time,in order to improve the position control accuracy and response speed of the system,and avoid overshoot,three fuzzy intelligent compound control algorithms are used to parameterize the position loop of the servo system.Tuning,namely adaptive fuzzy PID parameter online optimization tuning algorithm,gaintype adaptive fuzzy PID parameter online optimization tuning algorithm,PID parameter online optimization tuning algorithm based on the expert experience rule table,through the simulation and comparison analysis of the three algorithms,it is determined based on The PID parameter online optimization and tuning algorithm performance of the expert experience rule table is the best,and it is taken as the final solution.