Interference Suppression Algorithm for Microthrust Measurement System Based on Particle Swarm Optimization Fuzzy PID

Micronewton thrusters have a wide range of applications in the aerospace field, and the accuracy of micronewton thrust measurement is directly affected by environmental vibration. The cantilever beam is the core part of the microthrust measurement system, and its stability directly affects the accuracy of thrust calibration. Aiming at the problems of the cantilever beam oscillating during the change in thrust and being susceptible to the impulse vibration of the ground, the interference suppression scheme of the microthrust measurement system based on the fuzzy PID of particle swarm optimization is investigated. And an interference suppression algorithm of the microthrust system based on the adaptive Kalman displacement expectancy estimation algorithm and the fuzzy PID of particle swarm optimization is designed. An adaptive Kalman displacement expectation estimation algorithm and a particle swarm optimization fuzzy PID microthrust system interference suppression algorithm are designed. The results show that the proposed algorithm can effectively track the thrust signal and suppress the influence of external vibration interference for the mN-level thrust change, control the overshooting amount within 10%, shorten the stabilization time to within 0.2 s, reduce the impulse oscillation to 22% of the original, reduce the steady-state error, and have a strong suppression effect on the oscillation phenomenon of the system, with better control accuracy and stability, and provide a good condition for the thrust calibration.