Novel Nussbaum-Type Function based Safe Adaptive Distributed Consensus Control with Arbitrary Unknown Control Direction

TL;DR

This paper introduces a novel saturated Nussbaum function for multi-agent system consensus control, enabling safe, adaptive, and distributed consensus with arbitrary unknown control directions, reducing control shocks.

Contribution

It develops a new saturated Nussbaum function and control scheme that relaxes previous limitations, ensuring safe and smooth consensus in multi-agent systems with diverse unknown control directions.

Findings

Achieves bounded and asymptotically convergent signals in the closed-loop system.

Demonstrates smaller control shock amplitudes compared to traditional methods.

Validates effectiveness through numerical simulations.

Abstract

Existing Nussbaum function based methods on the consensus of multi-agent systems require (partial) identical unknown control directions of all agents and cause dangerous dramatic control shocks. This paper develops a novel saturated Nussbaum function to relax such limitations and proposes a Nussbaum function based control scheme for the consensus problem of multi-agent systems with arbitrary non-identical unknown control directions and safe control progress. First, a novel type of the Nussbaum function with different frequencies is proposed in the form of saturated time-elongation functions, which provides a more smooth and safer transient performance of the control progress. Furthermore, the novel Nussbaum function is employed to design distributed adaptive control algorithms for linearly parameterized multi-agent systems to achieve average consensus cooperatively without dramatic control shocks. Then, under the undirected connected communication topology, all the signals of the closed-loop systems are proved to be bounded and asymptotically convergent. Finally, two comparative numerical simulation examples are carried out to verify the effectiveness and the superiority of the proposed approach with smaller control shock amplitudes than traditional Nussbaum methods.