11,114 research outputs found
LMI-based design of state-feedback controllers for pole clustering of LPV systems in a union of -regions
This paper introduces an approach for the design of a state-feedback controller that achieves pole clustering in a union of DR-regions for linear parameter varying systems. The design conditions, obtained using a partial pole placement theorem, are eventually expressed in terms of linear matrix inequalities. In addition, it is shown that the approach can be modified in a shifting sense. Hence, the controller gain is computed such that different values of the varying parameters imply different regions of the complex plane where the closed-loop poles are situated. This approach enables the online modification of the closed-loop performance. The effectiveness of the proposed method is demonstrated by means of simulations.Peer ReviewedPostprint (author's final draft
LMI-based design of state-feedback controllers for pole clustering of LPV systems in a union of DR-regions
This paper introduces an approach for the design of a state-feedback controller that achieves pole clustering in a union of DR-regions for linear parameter varying systems. The design conditions, obtained using a partial pole placement theorem, are eventually expressed in terms of linear matrix inequalities. In addition, it is shown that the approach can be modified in a shifting sense. Hence, the controller gain is computed such that different values of the varying parameters imply different regions of the complex plane where the closed-loop poles are situated. This approach enables the online modification of the closed-loop performance. The effectiveness of the proposed method is demonstrated by means of simulations.acceptedVersio
H2 Optimal Coordination of Homogeneous Agents Subject to Limited Information Exchange
Controllers with a diagonal-plus-low-rank structure constitute a scalable
class of controllers for multi-agent systems. Previous research has shown that
diagonal-plus-low-rank control laws appear as the optimal solution to a class
of multi-agent H2 coordination problems, which arise in the control of wind
farms. In this paper we show that this result extends to the case where the
information exchange between agents is subject to limitations. We also show
that the computational effort required to obtain the optimal controller is
independent of the number of agents and provide analytical expressions that
quantify the usefulness of information exchange
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