摘要
基于滞环齿隙模型和集合摩擦模型,建立了齿轮传动系统动力学变结构模型。采用径向基函数(RBF)神经网络和滑模控制构成复合控制器,对系统齿隙、摩擦非线性因素进行了补偿。利用RBF神经网络调节滑模控制器的切换项增益,降低了滑模控制的抖振,提高了补偿效果,仿真结果验证了该方法的可行性。
A variable structure dynamic model of gear driving system is established based on backlash hysteresis model and friction aggregation model. The influence of backlash and friction is compensated based on a compound controller formed by radial basis function （RBF） neural network and sliding mode. The switching plus of sliding mode controller can be adjusted by RBF neural network, which can reduce the buffeting of sliding mode control. The feasibility of this method is validated by simulation results.
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2008年第5期793-796,共4页
Journal of University of Electronic Science and Technology of China
基金
国家自然科学基金(10476019)
关键词
齿隙
补偿
摩擦
RBF神经网络
滑模控制
backlash
compensation
friction
RBF neural network
sliding mode control
