Non-linear system modelling based on NARX model expansion on Laguerre orthonormal bases

被引:16
作者
Benabdelwahed, Imen [1 ]
Mbarek, Abdelkader [1 ]
Bouzrara, Kais [1 ]
Garna, Tarek [1 ]
机构
[1] Univ Monastir, Natl Sch Engineers Monastir, Res Lab Automat Signal & Image Proc, Ave Avicenne, Monastir 5019, Tunisia
关键词
nonlinear systems; autoregressive processes; mean square error methods; minimisation; genetic algorithms; poles and zeros; discrete time systems; nonlinear system modelling; NARX model expansion; Laguerre orthonormal bases; discrete nonlinear autoregressive with exogenous inputs model; crossed product; autoregressive product; exogenous product; parameter number reduction; genetic algorithm; NARX-Laguerre poles; normalised mean square error minimisation; optimisation algorithm; numerical simulations; benchmark continuous stirred tank reactor; nonlinear discrete time system; PARAMETER-ESTIMATION ALGORITHMS; IDENTIFICATION; DECOMPOSITION;
D O I
10.1049/iet-spr.2017.0187
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This study proposes a new representation of discrete Non-linear AutoRegressive with eXogenous inputs (NARX) model by developing its coefficients associated to the input, the output, the crossed product, the exogenous product and the autoregressive product on five independent Laguerre orthonormal bases. The resulting model, entitled NARX-Laguerre, ensures a significant parameter number reduction with respect to the NARX model. However, this reduction is still subject to an optimal choice of the Laguerre poles defining the five Laguerre bases. Therefore, the authors propose to use the genetic algorithm to optimise the NARX-Laguerre poles, based on the minimisation of the normalised mean square error. The performances of the resulting NARX-Laguerre model and the proposed optimisation algorithm are validated by numerical simulations and tested on the benchmark Continuous Stirred Tank Reactor.
引用
收藏
页码:228 / 241
页数:14
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