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Communication Dans Un Congrès Année : 2022

Adaptive Control/Identification for Hybrid Systems, Part II: with Linear-growth-order Discrete Regressor

Résumé

In this and the companion paper [1] we propose a direct-adaptive-control framework for hybrid dynamical systems with unknown parameters. The approach addresses both the tracking-control and the parameter-estimation problems and relies on Lyapunov theory for hybrid systems. In this paper, we extend the main results of [1] to deal with hybrid systems that contain a regressor that is of linear order of growth, thereby relaxing the boundedness restriction imposed in [1]. As in the latter reference, the statements rely on Lyapunov theory for hybrid systems and we establish uniform global asymptotic stability in closed loop. In particular, parameterestimation convergence is guaranteed when a generic hybrid persistence of excitation condition on the pair of discrete and continuous regressor functions holds. On the other hand, the relaxation of the boundedness assumption relies on a higherorder adaptation law.

Domaines

Automatique
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Dates et versions

hal-03789105 , version 1 (27-09-2022)

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Mohamed Maghenem, Adnane Saoud, Antonio Loria. Adaptive Control/Identification for Hybrid Systems, Part II: with Linear-growth-order Discrete Regressor. 2022 American Control Conference (ACC 2022), Jun 2022, Atlanta, GA, United States. ⟨10.23919/ACC53348.2022.9867414⟩. ⟨hal-03789105⟩
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