基于粒子群优化自抗扰控制的舵系统研究

舰载诱饵干扰弹作为重要的防御性武器，其舵系统对保证飞行控制系统的动态品质和飞行安全具有核心作用。传统的 PID 控制算法在抗干扰能力和快速响应能力方面存在局限性。为此引入粒子群优化技术并集成自抗扰和智能算法的优势，以改进自抗扰控制算法，提高舵系统的抗干扰能力和稳定性。针对自抗扰控制存在的离线调节问题，提出使用粒子群智能算法在线优化舵系统控制器的参数，以适应环境变化及时调整，解决控制性能受限问题。系统的仿真实验结果显示，与传统的 PID 算法和 ADRC 算法相比，基于粒子群优化的自抗扰控制方法在舵系统位置环控制中拥有更优的性能。

Research on Rudder Systems Based on Particle Swarm Optimization Active Disturbance Rejection Control

As an important defensive weapon，the rudder system of shipborne decoy jamming missile plays a key role in ensuring the dynamic quality and flight safety of the flight control system. Traditional PID control algorithms have limitations in terms of anti-interference and fast response capabilities. Therefore，the particle swarm optimization technology is introduced and the advantages of active disturbance rejection and intelligent algorithms are integrated to improve the active disturbance rejection control algorithm and to enhance the anti-interference capability and stability of the rudder system. In view of the offline adjustment problem of self-disturbance rejection control，particle swarm intelligence algorithm is proposed to optimize the parameters of the rudder system controller online to adapt to environmental changes and to solve the problem of limited control performance. The simulation results of the system show that compared with traditional PID algorithm and ADRC algorithm，the active disturbance rejection control method based on particle swarm optimization has better performance in the position loop control of the rudder system.