Distributed event-triggered for adaptive neural network containment control of uncertain Euler–Lagrange systems with external disturbances. (October 2022)

• Record Type: Journal Article
• Authors: Wang, Qiangde; Zhang, Yang; Wei, Chunling
• Is Part Of: Transactions of the Institute of Measurement and Control. Volume 44:Number 14(2022)
• Page Start: 2768
• Page End: 2780
• Publication Date: 2022-10
• Subjects: Neural network -- event-triggered control -- containment control -- Euler–Lagrange systems; Automatic control -- Periodicals; Measuring instruments -- Periodicals; Commande automatique -- Périodiques; Mesure -- Instruments -- Périodiques; 681.2
• DOI: 10.1177/01423312221088656
• Languages: English
• ISSNs: 0142-3312

Abstract

This paper investigates the containment control problem for multiple Euler–Lagrange systems with unknown time-varying disturbances over directed graphs, in which the dynamics of leaders and followers are heterogeneous. First of all, the expected output signals of leaders can only be acquired by some subsystems owing to the limited communication conditions, and the output adjustment errors are obtained indirectly by other subsystems through the network connection. In consequence, a compensator based on relative output information is designed to estimate a trajectory inside the convex hull spanned by states of the leaders. Second, a fully distributed event-triggered adaptive control scheme is proposed, and a disturbance estimator is designed to achieve interference suppression. In addition, the design of the overall control protocol does not use the relative speed of the followers. Finally, a dual-axis manipulator is taken as an example to validate the effectiveness of the proposed control scheme.