Stable-inversion based iterative learning control for non-minimum phase plants
基于稳定逆的非最小相位系统的迭代学习控制

In order to deal with the poor tracking effect which occurs when the iterative learning control (ILC) was applied to the non-minimum phase system, an optimal ILC scheme with current feedback was presented for linear non-minimum phase plants based on an optimality criterion and noncausal stable inversion. The convergence of this scheme was analyzed and the utility mode of using the noncausal algorithm was proposed for the practical application.