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Adaptive Appointed-Time Consensus Control of Networked Euler-Lagrange Systems With Connectivity Preservation.
IEEE Trans Cybern ; 52(11): 12379-12392, 2022 Nov.
Article en En | MEDLINE | ID: mdl-34029204
ABSTRACT
With consideration of motion control performance and efficient information communication, the synchronization problem on communication connectivity preservation and guaranteed consensus performance for networked mechanical systems has attracted considerable attention in recent years. Different from the existing works, this article investigates a brand-new appointed-time consensus control approach for uncertain networked Euler-Lagrange systems on a directed graph via exploring the prescribed performance control structure. First, a two-layer prescribed performance envelope is formulated via using an appointed-time convergent function for position-related and velocity-related consensus errors, respectively. Then, a simple state-feedback virtual controller with online adaptive performance adjustment is developed to preserve the communication connectivity. Moreover, to guarantee the velocity consensus of the networked systems and improve the position consensus accuracy, an appointed-time adaptive controller is designed by applying the norm inequality to the system uncertainties and external disturbances. Compared to the existing consensus control approaches, the prime advantage of the proposed one is that the constraints generated from the communication ranges are approximated by a time-varying contractive performance envelope, wherein, the appointed-time convergence and steady-state tracking accuracy are preassigned a priori. Meanwhile, no repeated logarithmic error transformations are required in the relevant controller design, which implies that the complexity of the devised control laws has decreased dramatically. Finally, two groups of illustrative examples are organized to validate the effectiveness of the proposed consensus control approach.

Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: IEEE Trans Cybern Año: 2022 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: IEEE Trans Cybern Año: 2022 Tipo del documento: Article