An EM Algorithm for Lebesgue-sampled State-space Continuous-time System Identification

被引:1
|
作者
Gonzalez, Rodrigo A. [1 ]
Cedeno, Angel L. [2 ,3 ]
Coronel, Maria [3 ]
Aguero, Juan C. [2 ,3 ]
Rojas, Cristian R. [4 ]
机构
[1] Eindhoven Univ Technol, Dept Mech Engn, Eindhoven, Netherlands
[2] Univ Tecn Federico Santa Maria, Elect Engn Dept, Valparaiso, Chile
[3] Adv Ctr Elect & Elect Engn AC3E, Valparaiso, Chile
[4] KTH Royal Inst Technol, Div Decis & Control Syst, Stockholm, Sweden
来源
IFAC PAPERSONLINE | 2023年 / 56卷 / 02期
基金
瑞典研究理事会;
关键词
System identification; continuous-time systems; event-based sampling; expectation-maximization; MODELS;
D O I
10.1016/j.ifacol.2023.10.1771
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 concerns the identification of continuous-time systems in state-space form that are subject to Lebesgue sampling. Contrary to equidistant (Riemann) sampling, Lebesgue sampling consists of taking measurements of a continuous-time signal whenever it crosses fixed and regularly partitioned thresholds. The knowledge of the intersample behavior of the output data is exploited in this work to derive an expectation-maximization (EM) algorithm for parameter estimation of the state-space and noise covariance matrices. For this purpose, we use the incremental discrete-time equivalent of the system, which leads to EM iterations of the continuous-time state-space matrices that can be computed by standard filtering and smoothing procedures. The effectiveness of the identification method is tested via Monte Carlo simulations.
引用
收藏
页码:4204 / 4209
页数:6
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