Robust offset-free constrained Model Predictive Control with Long Short-Term Memory Networks -- Extended version
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| _version_ | 1866917814920544256 |
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| author | Schimperna, Irene Magni, Lalo |
| author_facet | Schimperna, Irene Magni, Lalo |
| contents | This paper develops a control scheme, based on the use of Long Short-Term Memory neural network models and Nonlinear Model Predictive Control, which guarantees recursive feasibility with slow time variant set-points and disturbances, input and output constraints and unmeasurable state. Moreover, if the set-point and the disturbance are asymptotically constant, offset-free tracking is guaranteed. Offset-free tracking is obtained by augmenting the model with a disturbance, to be estimated together with the states of the Long Short-Term Memory network model by a properly designed observer. Satisfaction of the output constraints in presence of observer estimation error, time variant set-points and disturbances is obtained using a constraint tightening approach. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2303_17304 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Robust offset-free constrained Model Predictive Control with Long Short-Term Memory Networks -- Extended version Schimperna, Irene Magni, Lalo Systems and Control This paper develops a control scheme, based on the use of Long Short-Term Memory neural network models and Nonlinear Model Predictive Control, which guarantees recursive feasibility with slow time variant set-points and disturbances, input and output constraints and unmeasurable state. Moreover, if the set-point and the disturbance are asymptotically constant, offset-free tracking is guaranteed. Offset-free tracking is obtained by augmenting the model with a disturbance, to be estimated together with the states of the Long Short-Term Memory network model by a properly designed observer. Satisfaction of the output constraints in presence of observer estimation error, time variant set-points and disturbances is obtained using a constraint tightening approach. |
| title | Robust offset-free constrained Model Predictive Control with Long Short-Term Memory Networks -- Extended version |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2303.17304 |