Highly efficient identifiability, controllability & observability detection of large-scale nonlinear dynamical systems.
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Citar como
Gerard Van Willigenburg (2026). Identifiability, controllability & observability detection. (https://la.mathworks.com/matlabcentral/fileexchange/106000-identifiability-controllability-observability-detection), MATLAB Central File Exchange. Recuperado .
Información general
- Versión 1.3.0 (56,5 KB)
Compatibilidad con la versión de MATLAB
- Compatible con cualquier versión
Compatibilidad con las plataformas
- Windows
- macOS
- Linux
| Versión | Publicado | Notas de la versión | Action |
|---|---|---|---|
| 1.3.0 | nlident now properly handles indices to be estimated initial state variables as in the additional example on identifiability of the NFKappaB model. Plots have been improved. Sundials integrators are now supported too. |
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| 1.2.5 | Link updated |
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| 1.2.4 | Link updated |
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| 1.2.3 | figureFullScreen deleted figure used |
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| 1.2.2 | Line 92 of fxusen.m updated to also include uxNtr. Makes a difference only when nx0=1 is selected as an input to nlacchs. Instead of local strong accessibility this checks local accessibility. |
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| 1.2.1 | The number of samples ns making up the sensitivity matrices in nlacchs, nlident is by default set to nx, npx, the maximum if all but one input/parameter is "disconnected". Script exmrhs now also calls function nlacchs. |
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| 1.2.0 | The number of default samples ns to build the sensitivity matrix in nlacchs is updated to not depend on the number of system inputs nu (since an arbitrary number of inputs may be disconnected causing uncontrollability). |
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| 1.1.0 | Update readme, dnkwbl64 (correction obtained from Jinrae Kim), nlacchs (output argument uxNcr added). |
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| 1.0.0 |
