论文标题
具有任意或限制切换的开关线性系统识别的有限样本分析
Finite-sample analysis of identification of switched linear systems with arbitrary or restricted switching
论文作者
论文摘要
为了识别具有测量开关信号的开关系统，该工作旨在分析切换策略对估计误差的影响。假定识别数据是从全球渐近或边缘稳定的开关系统中收集的开关，该系统是任意或受到平均停留时间约束的。然后由最小二乘（LS）估计器估算开关系统。为了捕获开关策略参数对LS估计误差的影响，在这项工作中开发了有限样本误差界。获得的误差界表明，估计误差仅有稳定模式时开关参数的对数。但是，当有不稳定的模式时，随着开关参数的变化，估计误差界限可能会线性增加。这表明在存在不稳定模式的情况下，应正确设计开关策略，以避免估计误差的显着增加。
For the identification of switched systems with a measured switching signal, this work aims to analyze the effect of switching strategies on the estimation error. The data for identification is assumed to be collected from globally asymptotically or marginally stable switched systems under switches that are arbitrary or subject to an average dwell time constraint. Then the switched system is estimated by the least-squares (LS) estimator. To capture the effect of the parameters of the switching strategies on the LS estimation error, finite-sample error bounds are developed in this work. The obtained error bounds show that the estimation error is logarithmic of the switching parameters when there are only stable modes; however, when there are unstable modes, the estimation error bound can increase linearly as the switching parameter changes. This suggests that in the presence of unstable modes, the switching strategy should be properly designed to avoid the significant increase of the estimation error.
