ARX modeling of unstable linear systems

作者：Galrinho Miguel^*; Everitt Niklas; Hjalmarsson Hakan

来源：Automatica, 2017, 75: 167-171.

DOI：10.1016/j.automatica.2016.09.041

• System identification
• Polynomial models
• Closed-loop identification

High-order ARX models can be used to approximate a quite general class of linear systems in a parametric model structure, and well-established methods can then be used to retrieve the true plant and noise models from the ARX polynomials. However, this commonly used approach is only valid when the plant is stable or if the unstable poles are shared with the true noise model. In this contribution, we generalize this approach to allow the unstable poles not to be shared, by introducing modifications to correctly retrieve the noise model and noise variance.

• 出版日期2017-1