A New Robust Adaptive Decentralized Tube Model Predictive Control of Continuous Time Uncertain Nonlinear Large-Scale Systems
In this paper, a new decentralized model predictive control has been proposed for continuous-time nonlinear large-scale systems made of multiple interconnected subsystems and uncertain systems with disturbances. This approach is characterized by: (I) consideration of input and state constraints, (II...
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| Autores principales: | , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Taylor & Francis Group
2019
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/5c66b7d55601409a94b5dbeafcc042a8 |
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| Sumario: | In this paper, a new decentralized model predictive control has been proposed for continuous-time nonlinear large-scale systems made of multiple interconnected subsystems and uncertain systems with disturbances. This approach is characterized by: (I) consideration of input and state constraints, (II) no requirement for information transmission between local control rules, (III) robustness of local controllers to uncertainty in model and disturbances.; (IV) bounded disturbances in subsystems, but their upper bound is not specified; (V) a robust invariant set for each controller; (VI) proven closed-loop system overall stability and convergence. In order to show the key features and the performance of the proposed algorithm, a simulation model has been provided. |
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