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针对不确定性系统提出一种非因果鲁棒学习控制方法.该学习控制律的非因果学习部分通过标称系统的优化指标得到,鲁棒部分通过设计鲁棒加权来实现.首先,不考虑鲁棒部分的具体形式,推导出标称系统描述的学习控制律的鲁棒收敛性条件;然后,设计与系统不确定性相关的鲁棒加权,由鲁棒收敛性条件得到鲁棒加权的设计原则;最后,通过仿真实验验证了所提出方法的有效性,并分析了不同形式不确定性系统鲁棒设计的保守性.
A non-causal robust learning control method is proposed for the uncertain system. The non-causal learning part of the learning control law is obtained through the optimization index of the nominal system and the robust part is designed by designing the robust weighting.First, The concrete form of the bar part, and derive the robust convergence condition of the learning control law described by the nominal system. Then, we design the robust weightings related to the system uncertainty and the robust weighting design principles by the robust convergence condition Finally, the effectiveness of the proposed method is verified through simulation experiments, and the conservativeness of robust design of uncertain systems with different forms is analyzed.