基于干扰观测器的机电伺服系统PI控制策略

空气舵机电伺服系统的主要任务是接收控制指令，并驱动负载按指令角度摆动，在各类航空航天飞行器中具有越来越广泛的应用价值。然而在运行过程中存在的未知干扰给机电伺服系统高精度控制带来了巨大挑战。针对这一问题，提出基于干扰补偿的空气舵机伺服系统控制策略。首先进行空气舵机电伺服系统模型分析，其次运用径向基函数设计神经网络的状态观测器，将不可测量的舵面角度用估计值替代进行反馈控制，最后应用Lyapunov方法分析了有限时间收敛条件。仿真结果表明：与传统电机角度反馈相比，所提出的控制策略使空气舵机电伺服系统的稳态误差减少97%以上。

Interference Observer-Based PI Control Strategy of Electromechanical Servo System

The main task of air rudder electromechanical servo system is to receive control commands and drive the load to swing at the commanded angle,which has an increasingly wide range of applications in various aerospace vehicles.However,the unknown disturbances in the operation process bring great challenges to the high-precision control of electromechanical servo systems.To address this problem,an air rudder servo system control strategy was proposed based on disturbance compensation.The model analysis of the air servo motor servo system was carried out.The radial-basis-function-based neural network state observer was designed to replace the unmeasurable rudder angle with the estimated value for feedback control.Finally,the finite-time convergence condition was analyzed by applying the Lyapunov method.The simulation results show that the proposed control strategy reduces the steady-state error of the air rudder servo system by more than 97% compared to the conventional motor angle feedback.