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Carolina Albea

Publications and source records attributed to Carolina Albea.

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Robust stabilization of time-delay discrete switched affine systems via a predictive switching control law

This paper addresses the robust control of uncertain discrete-time switched affine systems subject to a single unitary input delay. The unique feature of this class of systems lies in the fact that the control input is the switching signal, which belongs to a finite set of values. Consequently, the closed-loop trajectories do not converge to an equilibrium point but rather to a limit cycle. To mitigate the impact of the input delay, we propose a min-switching predictive control approach, which is based on the known nominal dynamical characteristics of each mode. The objective of this approach is to ensure the robust stabilization of the uncertain system using this nominal predictor, employing a Lyapunov argument. Our main result provides tractable robust stabilization conditions that guarantee the convergence to a robust limit cycle under system uncertainties and delayed switching. Additionally, an optimization procedure has been incorporated to minimize the size of the attractor, which represents the region where the trajectories asymptotically converge. A numerical example validates the effectiveness of the proposed approach.

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Robust predictive control design for uncertain discrete switched affine systems subject to an input delay

Robust stabilization conditions for uncertain switched affine systems subject to a unitary input delay are presented. They are obtained through the Lyapunov framework and a min-switching state-feedback predictive control law. The result relies on a prediction scheme considering nominal system parameters. By constructing a Lyapunov function that considers the prediction error, we demonstrate the exponential convergence of the system trajectories and system prediction to a robust limit cycle. An example is provided to validate the obtained result.

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LMI relaxations and its application to data-driven control design for switched affine systems

The problem of data-driven control is addressed here in the context of switched affine systems. This class of nonlinear systems is of particular importance when controlling many types of applications in electronic, biology, medicine, etc. Still in the view of practical applications, providing an accurate model for this class of systems can be a hard task, and it might be more relevant to work on data issued from some trajectories obtained from experiments and to deploy a new branch of tools to stabilize the systems that are compatible with the processed data. Following the recent concept of data-driven control design, this paper first presents a generic equivalence lemma that shows a matrix constraint based on data, instead of the system parameter. Then, following the concept of robust hybrid limit cycles for uncertain switched affine systems, robust model-based and then data-driven control laws are designed based on a Lyapunov approach. The proposed results are then illustrated and evaluated on an academic example.

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