Output feedback robust distributed model predictive control for parallel systems in process networks with competitive characteristics
Output feedback robust distributed model predictive control for parallel systems in process networks with competitive characteristics
- Neue Suche nach: Zhang, S
- Neue Suche nach: Zhao, D
- Neue Suche nach: Spurgeon, SK
- Neue Suche nach: Zhang, S
- Neue Suche nach: Zhao, D
- Neue Suche nach: Spurgeon, SK
The parallel structure is one of the basic system architectures found in process networks. This paper formulates control strategies for such parallel systems when the states are unmeasured. The competitive coupling and competitive constraints are addressed in the control design. A distributed buffer and pre-estimator are proposed to solve problems relating to coupling and timely communication whilst a distributed moving horizon estimator is employed to further improve the estimation accuracy in the presence of the constraints. An output feedback robust distributed model predictive control algorithm is then developed for such parallel systems. The Lyapunov method is used for the theoretical analysis which produces tractable linear matrix inequalities (LMI). Simulations and experimental results are provided to validate the effectiveness of the proposed approach.
Dokumentinformationen
Output feedback robust distributed model predictive control for parallel systems in process networks with competitive characteristics
2021-08-01
Control Engineering Practice , 113 , Article 104842. (2021)
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
| DDC: | 629 |
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