Bounds on Prediction Error When Using an Impulse Response/Equilibrium Model Structure
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arXiv
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866913172055654400 |
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| author | Vincent, Tyrone L. Wakin, Michael B. |
| author_facet | Vincent, Tyrone L. Wakin, Michael B. |
| contents | An impulse response/equilibrium model (IREM) structure combines a linear convolution model with a nonlinear function that sets the current operating point via an equilibrium variable with integrator dynamics. This model structure is well suited for mildly nonlinear systems and in particular has been applied to battery fast charging control. This paper provides observability conditions for the IREM model structure and bounds on the prediction error. These conditions can be evaluated directly on the system impulse response. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_30691 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Bounds on Prediction Error When Using an Impulse Response/Equilibrium Model Structure Vincent, Tyrone L. Wakin, Michael B. Systems and Control Optimization and Control An impulse response/equilibrium model (IREM) structure combines a linear convolution model with a nonlinear function that sets the current operating point via an equilibrium variable with integrator dynamics. This model structure is well suited for mildly nonlinear systems and in particular has been applied to battery fast charging control. This paper provides observability conditions for the IREM model structure and bounds on the prediction error. These conditions can be evaluated directly on the system impulse response. |
| title | Bounds on Prediction Error When Using an Impulse Response/Equilibrium Model Structure |
| topic | Systems and Control Optimization and Control |
| url | https://arxiv.org/abs/2605.30691 |