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针对高速飞机飞行在大气干扰下,产生强烈阵风干扰,飞机方程存在未建模扰动,传统PID难以保证控制稳定效果,提出了基于粒子群优化策略的CMAC-PID并行控制的直接升力控制方法,并将其应用于飞机阵风减缓控制系统的设计中。采用乘坐品质舒适指数作为适应度函数,通过粒子群优化,得到PID控制器参数为神经网络训练提高导师信号。在系统运行中,PID控制器输出逐渐趋近为零,CMAC网络控制输出逐步取代PID控制输出,成为控制器主要控制信号。仿真结果表明,提出的方法比传统PID控制器能够更加有效的起到阵风减缓效果增加稳定性。
Aiming at the strong gust disturbance caused by the high-speed aircraft flight in the atmosphere, the aircraft equation has un-modeled disturbance and the traditional PID can not guarantee the control stability. A direct lift control method based on particle swarm optimization (CMPS-PID) parallel control is proposed. It is applied to the design of aircraft gust mitigation control system. By using the comfort index of riding quality as fitness function, the parameters of PID controller are obtained by neural network training to improve the mentor signal through particle swarm optimization. In the system operation, the PID controller output gradually approaches zero, and the CMAC network control output gradually replaces the PID control output and becomes the main control signal of the controller. The simulation results show that the proposed method can increase the stability of the gust mitigation effect more effectively than the traditional PID controller.