Nonlinear system identification using a cuckoo search optimized adaptive Hammerstein model

作者：

Highlights：

• A novel nonlinear system identification scheme is proposed.

• A Hammerstein model has been trained using cuckoo search algorithm.

• The model is a cascade of a FLANN and an adaptive IIR filter.

• Simulation study shows enhanced modeling capacity of the proposed scheme.

• The new schemes offers lesser computational time over other methods studied.

摘要

•A novel nonlinear system identification scheme is proposed.•A Hammerstein model has been trained using cuckoo search algorithm.•The model is a cascade of a FLANN and an adaptive IIR filter.•Simulation study shows enhanced modeling capacity of the proposed scheme.•The new schemes offers lesser computational time over other methods studied.

论文关键词：Hammerstein model,System identification,Particle swarm optimization algorithm,Differential evolution,Cuckoo search algorithm

论文评审过程：Available online 4 November 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2014.10.040