Nonlinear Identification for Control by Using HARMAX Models

Janetta Culita,Dan Stefanoiu, Andreea-Maria Nica

2023 9th International Conference on Control, Decision and Information Technologies (CoDIT)(2023)

引用 0|浏览0
暂无评分
摘要
The purpose of this article is to perform a comparison between two identification models: a nonlinear one referred to as HARMAX and a classical linear one, of Box-Jenkins (BJ) type. The first model modifies a classical ARMAX model by applying Hammerstein polynomials on input, output, and noise signals. Identification of models was performed by means of Multi-Step Least Squares Method, as described into the article. The simulations on a real-world plant, namely ASTANK2, a fluidic system with two inputs, two outputs and nonlinear static characteristic, have proven that the HARMAX model performs better than the BJ model and provides more accurate useful models to be integrated into closed loop configurations.
更多
查看译文
关键词
Nonlinear identification,Hammerstein models,Multi-Step Least Squares Method,Cuckoo search
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要