基于PID神经网络控制器的飞控系统设计  

Design of Flight Control System Based on PIDNN

作　　者：黄小安[1] 艾剑良[1] 罗昌行[1] 

机构地区：[1]复旦大学

出　　处：《微计算机信息》2008年第22期10-12,共3页Control & Automation

基　　金：先进战斗机综合设计的关键技术研究(NCET-05-0357)

摘　　要：BP神经网络已被广泛应用于PID控制器的优化调参,但这种调参方法具有收敛速度慢、学习时间长、连接权重初值为随机值、易于陷入局部极小等缺点。本文提出了一种不同于用BP网络调整PID参数的新的融合方法:PID神经网络控制器(PIDNN);该控制器不仅能克服以上缺点,而且具有很好的鲁棒性。本文对PIDNN在某无人机姿态控制系统的应用进行了仿真研究,仿真结果表明该控制器能够大大地改善姿态控制系统性能。The neural network with BP algorithm has these disadvantages, such as slow convergence rate, long learn time, local opti- mization and random Value for the initial weight of the net, although it has been widely applied to regulate the parameters of PID controller. A new type of controller called PIDNN, which coalesces traditional PID and neural network together, is introduced in this paper. It overcomes these shortcomings mentioned and has better robustness. Then it is used in the flight control system of UAV, the simulation results show that it improves the performance of the system effectively.

关 键 词：飞行控制 姿态控制 PID神经网络控制器 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]