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系统地讨论了ＳＩＳＯ、线性时不变、指数稳定系统在最坏情况下的ｌ１鲁棒辨识问题。提出了系统模型集合的最小外框概念；建立了两种任意非零信号作用下ｌ１鲁棒辨识算法；提出了任意非零信号作用下系统的可辨识条件；证明了算法的全局收敛性和最优性。
This paper systematically discusses the l1 robust identification problem under the worst case of SISO, linear invariant and exponential stability. Proposed the minimum outer frame concept of system model set; established two kinds of non-zero signal under the action of l1 robust identification algorithm; proposed any non-zero signal under the system’s identifiable conditions; proved the global convergence of the algorithm and the most Excellent.