Adaptive time‐varying formation control of uncertain Euler–Lagrange systems with event‐triggered communication

Abstract

This article is concerned with time-varying formation control of networked Euler-Lagrange systems in the presence of unknown system parameters and event-triggered communication. Under a directed graph condition, a novel distributed adaptive formation control scheme is proposed. In order to reduce the communication burden among connected agents, a dynamic triggering condition is designed without the need of continuous monitoring of neighboring states. Zeno behavior that may exist in each agent can be rigorously excluded by introducing a dynamic variable into the triggering condition. It is shown that with the proposed control scheme, all the closed-loop signals are uniformly bounded and all the agents' generalized coordinates can form a time-varying formation configuration. The effectiveness of the proposed control scheme is validated with simulation results.

Event-triggered formation control of n-link networked stochastic robotic manipulators

“…Then, according to equation ( 35) and the definition of total candidate Lyapunov function equation (32), it can be concluded that all the signals z ½i i, 2 (t) in the closed-loop system are semi-globally uniformly bounded in the sense of the p = 4 moment, and signals…”

“…The ET control frameworks are also considered in investigating the formation of different forms of EL-MASs. [32][33][34] C4: in considering the ET control frameworks for nlink RM-MASs, the actuator levels of all manipulating links are simultaneously updated in previous studies. However, this results in redundant execution of events for some particular links that are working properly in accordance with the control objectives.…”

Synchronization control for multiple Euler–Lagrange systems in leader–follower framework under switching and event‐based communications

“…For instance, the event‐based algorithms are proposed in References 20‐22 for general linear MASs, in Reference 23 for second‐order MASs, in References 24 and 25 for output regulation of MASs. Formation control of uncertain Euler–Lagrange systems has been studied in Reference 26 with event‐based communication. In Reference 4, task‐space consensus of networked Euler–Lagrange is studied under both event‐based control and event‐based communication.…”

Adaptive extreme learning machine‐based event‐triggered control for perturbed Euler–Lagrange systems

“…In other words, the event‐triggered control approaches can balance the control system performance and the usage of actuation and communication resources. Recently, the designs of trajectory tracking control under event‐triggered framework have been explored by a quality of works for Euler–Lagrange systems 33‐38 . In References 33‐35, adaptive technique combined by neural network‐based sliding mode control techniques was developed to construct event‐triggered control strategies for dealing with trajectory tracking control problems of the uncertain Euler–Lagrange system.…”

“…Recently, the designs of trajectory tracking control under event‐triggered framework have been explored by a quality of works for Euler–Lagrange systems 33‐38 . In References 33‐35, adaptive technique combined by neural network‐based sliding mode control techniques was developed to construct event‐triggered control strategies for dealing with trajectory tracking control problems of the uncertain Euler–Lagrange system. The designs in References 36‐38 carried out distributed event‐triggered control approaches for multiple Euler–Lagrange systems to suppress the impacts of state/input saturation, parametric uncertainties, lacking relative velocity measurements, respectively.…”