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Uniform Asymptotic Stability and Slow Convergence in Adaptive Systems

机译:自适应系统中均匀的渐近稳定性和缓慢的收敛

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We examine convergence properties of errors in a class of adaptive systems that arises for scalar plants. We show that these adaptive systems are at best uniformly asymptotically stable in the large, and possess an infinite region where the trajectories move arbitrarily slowly, i.e. stick. We show that these properties are also exhibited by adaptive systems with closed-loop reference models which have been demonstrated to exhibit improved transient performance. Despite such transient behavior, we show that the slow convergence can still occur and has the potential to be slower than classic open-loop reference model adaptive systems.
机译:我们研究了一类用于标量植物的自适应系统中错误的收敛性。我们表明,这些自适应系统在大中是最均匀的渐近稳定,并且具有无限区域,其中轨迹慢慢地移动,即棒。我们表明,具有闭环参考模型的自适应系统也展示了这些性质,这些性能已经证明表现出改善的瞬态性能。尽管存在这种瞬态行为,但我们表明仍然可能发生缓慢的收敛性,并且可能与经典开环参考模型自适应系统慢慢。

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