摘要
稳像平台速度环的性能直接影响成像质量,本文提出了一种基于Elman网络和PD复合控制的自适应逆控制算法。通过对Elman网络模型和控制对象的分析,设计了独立的指令跟踪回路和干扰抑制回路,并将逆控制和PD复合控制思想应用在干扰抑制回路中,实现了Elman网络在线学习和对被控对象的在线辨识。仿真实验结果表明,该方法能有效克服系统慢时变、干扰等非线性因素的影响,增强系统的鲁棒性。
To satisfy the high performance of image-stabilization platform, a new compound adaptive inverse control method based on Elman neural network and PD was proposed for speed loop design. Through analysis of the Elman neural network model and the control object, index-trace loop and disturb-attenuation loop were designed independently. Training of the Elman neural network and identification of the object were implemented on line. Simulation results show that the method is feasible to effectively overcome the influences of the nonlinear factors, such as disturbances and the slow time-variation of parameters.
出处
《光电工程》
CAS
CSCD
北大核心
2008年第5期39-43,共5页
Opto-Electronic Engineering
基金
国家自然科学基金(60603097)支持项目
关键词
自适应控制
ELMAN网络
视轴稳定
逆控制
adaptive control
Elman neural network
line of sight stability
inverse control
