Task-space fixed-time bipartite tracking control for heterogeneous networked Euler-Lagrange systems

Abstract

This paper investigates the bipartite coordinated tracking control problem in the task-space of heterogeneous networked Euler-Lagrange systems in the fixed-time framework. A new neural network-based fixed-time hierarchical control approach is developed mainly under the directed graphs. Specifically, a distributed observer is firstly designed to estimate the desired position and velocity of the system in the fixed-time framework, and the neural network-based controller is proposed on this basis. The effect of system uncertainty is effectively mitigated and the chattering phenomenon is overcome, thus solving the bipartite coordinated tracking control problem of heterogeneous networked Euler-Lagrange systems at the control layer. In addition, the error can be kept within a small convergence region as derived by the fixed-time stability theory. Finally, the feasibility of the proposed control scheme is fully verified by numerical simulation.