In this paper, a decentralized model predictive control approach is proposed for discrete linear systems with a high number of inputs and states. The system is decomposed into several interacting subsystems. The interaction among subsystems is modeled as external disturbances. Then, using the concept of robust positively invariant ellipsoids, a robust model predictive control law is obtained for each subsystem solving several linear matrix inequalities. Maintaining the recursive feasibility while considering the attenuation of mutual coupling at each time step and the stability of the overall system are investigated. Moreover, an illustrative simulation example is provided to demonstrate the effectiveness of the method.

Decentralized Robust Model Predictive Control for Multi-Input Linear Systems

Pannocchia, Gabriele
2018

Abstract

In this paper, a decentralized model predictive control approach is proposed for discrete linear systems with a high number of inputs and states. The system is decomposed into several interacting subsystems. The interaction among subsystems is modeled as external disturbances. Then, using the concept of robust positively invariant ellipsoids, a robust model predictive control law is obtained for each subsystem solving several linear matrix inequalities. Maintaining the recursive feasibility while considering the attenuation of mutual coupling at each time step and the stability of the overall system are investigated. Moreover, an illustrative simulation example is provided to demonstrate the effectiveness of the method.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11568/940758
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