兵工自动化Issue(5)：60-62,67,4.DOI:10.7690/bgzdh.2013.05.016
参数自学习PID算法在电动负载模拟器中的应用
Application of Parameters Self-Learning PID Algorithm in Electric Load Simulator
王强 1王志胜1
作者信息
- 1. 南京航空航天大学自动化学院，南京 210016
- 折叠
摘要
Abstract
Due to the fact that surplus torque caused by the movement of rudder seriously affected load spectrum tracking accuracy of electric load simulator, feed forward control was used to compensate and suppress the surplus torque, and parameters self-learning PID algorithm based on BP neural network was used to achieve high-precision tracking of the load spectrum .The cause and effect of surplus torque to electric load simulator in the passive loading mode was explained, feed forward control based on structure invariance principle was used to compensate and suppress surplus torque caused by the movement of rudder. Based on feed forward control suppressing surplus torque, the limitations of traditional PID algorithm and static BP neural network were analyzed in the conditions of nonlinear and time-varying parameters. Self-learning PID control algorithm based on BP neural network was used to make PID parameters adjust online and to achieve high-precision tracking of the load spectrum. In the case of rudder interference, simulations on constant and sinusoidal load spectrum were tested respectively. The simulation results show that the control algorithm makes the electric load simulator could accurately and quickly track the load spectrum, improving the adaptability and robustness of the electric servo load simulator.关键词
负载模拟器/多余力矩/前馈控制/BP神经网络/参数自学习Key words
load simulator/surplus torque/feed forward compensation/BP neural network/parameter self-learning分类
军事科技引用本文复制引用
王强,王志胜..参数自学习PID算法在电动负载模拟器中的应用[J].兵工自动化,2013,(5):60-62,67,4.
