Direct identification of continuous-time linear switched state-space models

被引：0
|
作者：
Mejari, Manas [1 ]
Piga, Dario [1 ]
机构：
[1] USI SUPSI, IDSIA Dalle Molle Inst Artificial Intelligence, Via Santa 1, CH-6962 Lugano, Switzerland
来源：
IFAC PAPERSONLINE | 2023年 / 56卷 / 02期
关键词：
Continuous-time system estimation; Hybrid and switched systems modeling; PIECEWISE AFFINE REGRESSION;
D O I：
10.1016/j.ifacol.2023.10.1773
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents an algorithm for direct continuous-time (CT) identification of linear switched state-space (LSS) models. The key idea for direct CT identification is based on an integral architecture consisting of an LSS model followed by an integral block. This architecture is used to approximate the continuous-time state map of a switched system. A properly constructed objective criterion is proposed based on the integral architecture in order to estimate the unknown parameters and signals of the LSS model. A coordinate descent algorithm is employed to optimize this objective, which alternates between computing the unknown model matrices, switching sequence and estimating the state variables. The effectiveness of the proposed algorithm is shown via a simulation case study.
引用
收藏
页码：4210 / 4215
页数：6
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