A guided residual search for nonlinear state-space identification
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arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866910034023153664 |
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| author | Floren, Merijn Swevers, Jan |
| author_facet | Floren, Merijn Swevers, Jan |
| contents | Parameter estimation of nonlinear state-space models from input-output data typically requires solving a highly non-convex optimization problem prone to slow convergence and suboptimal solutions. This work improves the reliability and efficiency of the estimation process by decomposing the overall optimization problem into a sequence of tractable subproblems. Based on an initial linear model, nonlinear residual dynamics are first estimated via a guided residual search and subsequently refined using multiple-shooting optimization. Experimental results on two benchmarks demonstrate competitive performance relative to state-of-the-art black-box methods and improved convergence compared to naive initialization. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_22964 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A guided residual search for nonlinear state-space identification Floren, Merijn Swevers, Jan Signal Processing Parameter estimation of nonlinear state-space models from input-output data typically requires solving a highly non-convex optimization problem prone to slow convergence and suboptimal solutions. This work improves the reliability and efficiency of the estimation process by decomposing the overall optimization problem into a sequence of tractable subproblems. Based on an initial linear model, nonlinear residual dynamics are first estimated via a guided residual search and subsequently refined using multiple-shooting optimization. Experimental results on two benchmarks demonstrate competitive performance relative to state-of-the-art black-box methods and improved convergence compared to naive initialization. |
| title | A guided residual search for nonlinear state-space identification |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2602.22964 |