航空发动机分数阶PID控制器的参数自整定方法

控制器作为航空发动机的大脑，是保障发动机正常运行的核心部件，随着对发动机控制器精度和时效性的要求越来越高，传统PID控制器的性能亟需进一步提升.本文提出了改进的分数阶PID离线和在线参数整定方法，应用于涡扇发动机推力的控制中.首先，利用Caputo分数阶微积分定义建立分数阶PID模型，实现时域上的数值计算；其次，基于对数正态分布提出了改进的布谷鸟算法，实现了分数阶PID离线参数整定；然后，结合RBF网络设计参数线上整定方法，解决了参数在线整定问题；最后将相关理论应用于发动机推力的控制中，结果表明，相比其他几种优化算法，改进的布谷鸟优化算法对分数阶PID控制参数整定效果最好；利用RBF神经网络对分数阶PID进行在线整定时控制效果稳定，且分数阶PID的控制效果优于传统的PID控制，能提高对推力的控制能力.

Parameter Self-Tuning Method of Fractional Order Pid Controller for The Aero Engine

As the key part of the aero engine, the controller is the core component to ensure the normal operation of the engine.With the development of aero engine, it requires higher and higher accuracy and timeliness of the control of aero engine, which promotes to increase the effectiveness of PID controller. In this work, two online and offline parameter self-tuning methods for fractional order PID are proposed to control the thrust of aero engine. Firstly, a fractional PID model is established based on the Caputo fractional calculus definition.Secondly,by introducing the lognormal distribution,an improved cuckoo optimization algorithm is provided to achieve offline parameter tuning.Then,combining with RBF network, the parameter online setting problem for fractional order PID is solved. Finally, the results show that the improved cuckoo optimization algorithm exhibits high performance on offline parameters tuning of fractional order PID. The online parameter tuning based on RBF neural network also works stably.We find that the control effect of fractional order PID is much better than the traditional PID,which greatly improves the thrust control effectiveness.