论文部分内容阅读
针对一类单输入单输出不确定非线性重复跟踪系统 ,提出一种基于完全未知控制增益的自适应迭代反馈控制 .与普通迭代学习控制需要学习增益稳定性前提条件不同 ,所提自适应迭代反馈控制律通过不断修改Nuss baum形式的反馈增益达到收敛 .证明当迭代次数i→δ时 ,重复跟踪误差可一致收敛到任意小界δ .仿真显示了所提控制方法的有效性 .
For a class of single-input single-output uncertain nonlinear repetitive tracking system, an adaptive iterative feedback control based on completely unknown control gain is proposed.Compared with ordinary iterative learning control, the preconditions for learning gain stability are different. The proposed adaptive iterative feedback The control law converges by constantly changing the feedback gain in the Nussbaum form, which shows that the iterative tracking error converges uniformly to any small boundary δ when the iteration times i → δ. Simulation shows the effectiveness of the proposed control method.