Neuro-adaptive augmented distributed nonlinear dynamic inversion for consensus of nonlinear agents with unknown external disturbance

Abstract

This paper presents a novel neuro-adaptive augmented distributed nonlinear dynamic inversion (N-DNDI) controller for consensus of nonlinear multi-agent systems in the presence of unknown external disturbance. N-DNDI is a blending of neural network and distributed nonlinear dynamic inversion (DNDI), a new consensus control technique that inherits the features of Nonlinear Dynamic Inversion (NDI) and is capable of handling the unknown external disturbance. The implementation of NDI based consensus control along with neural networks is unique in the context of multi-agent consensus. The mathematical details provided in this paper show the solid theoretical base, and simulation results prove the effectiveness of the proposed scheme.

Consensus Tracking of Nonlinear Agents Using Distributed Nonlinear Dynamic Inversion with Switching Leader-Follower Connection

“…The control action is generated by consensus protocols designed using control theory. Researchers have proposed a variety of consensus protocols to solve different categories of consensus problems considering linear and nonlinear agents, like communication issues (switching topology [ 6 , 7 , 8 ], delays [ 9 , 10 , 11 ], noise [ 12 , 13 , 14 ]), disturbance [ 15 , 16 ], and fault [ 17 , 18 ].…”

“…Mondal et al [ 14 ] proposed a distributed consensus protocol based on NDI and named it Distributed NDI or DNDI. It has been implemented to solve consensus problems with actuator fault [ 18 ], external disturbances [ 16 ], and bipartite consensus [ 52 ]. In this paper, we have proposed a variety of DNDI that exploits the tracking capability of NDI and successfully solves a leader–following consensus tracking problem, which is different from leaderless consensus in terms of concept and formulation.…”