OCSYSYApr 4, 2020

Modelling non-linear control systems using the discrete Urysohn operator

arXiv:1802.0170018 citationsh-index: 11
Originality Incremental advance
AI Analysis

For control engineers, this provides a new method for real-time identification of non-linear systems with guaranteed uniqueness, though the examples are limited.

The paper introduces a multiple-input discrete Urysohn operator for modeling non-linear control systems and an iterative identification procedure that yields a unique minimum-norm solution. The approach is demonstrated on a non-linear mechanical system and a real-world dynamic object.

This paper introduces a multiple-input discrete Urysohn operator for modelling non-linear control systems and a technique of its identification by processing the observed input and output signals. It is shown that, due to the nature of the discrete Urysohn operator, the identification problem always has an infinity of solutions, which exactly convert the inputs to the output. The suggested iterative identification procedure, however, leads to a unique solution with the minimum norm, requires only few arithmetic operations with the parameter values and is applicable to a real-time identification, running concurrently with the data reading. The efficiency of the proposed modelling and identification approaches is demonstrated using an example of a non-linear mechanical system, which is represented by a differential equation, and an example of a complex real-world dynamic object.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes