Adaptive Fast Finite-Time Consensus for Second-Order Uncertain Nonlinear Multi-Agent Systems With Unknown Dead-Zone

Abstract

This paper presents an adaptive fast finite-time consensus (FTC) for second-order uncertain nonlinear (UN) multi-agent systems (MASs) with unknown nonsymmetric dead-zone and external disturbances. In the process of control protocols design, based on the estimation of the dead-zone width that is obtained by using adaptive method, a fuzzy logic dead-zone compensator is adopted to deal with the nonsymmetric dead-zone input phenomenon. Combining finite-time control technique and Lyapunov's relevant theory, a new fast FTC protocol is developed. Based on the basis of radial basis function neural networks (RBFNNs) theories, the unknown nonlinear functions are approximated. Under the presented consensus protocols and adaptive laws, it can be proved that the position errors of arbitrary two agents can reach a small region of zero in finite time as well as the velocity errors. Ultimately, the effectiveness of the designed method is tested via two numerical examples.

Adaptive consensus for heterogeneous unknown nonlinear multi-agent systems with asymmetric input dead-zone: A finite-time approach

“…In Yang et al (2019), the finite-time consensus problem with output dead-zone is investigated for unknown nonlinear MASs. Adaptive finite-time consensus for second-order uncertain nonlinear MASs with external disturbances and unknown nonsymmetric dead-zone is considered by Ren et al (2020).…”

“…In contrast with Cai et al (2016), Ren et al (2020), and Zamanian et al (2020), the global information for MASs, containing the number of agents and the interaction topology information, is not used in the proposed protocol. In other words, the protocol design is fully distributed.…”

Mean‐square output consensus of heterogeneous multi‐agent systems with communication noises

“…The theoretical frameworks for the consensus problem of MAS were presented [1][2][3]. According to much of the previous literatures [4][5][6][7][8][9][10], the purpose of the consensus problem is to construct a physically achievable controller so that all the agents can eventually reach the specified region or remain in the same state.…”

“…Many previous studies have focused on the consensus of the state of homogeneous agents, such as low-order systems [5,6], leader-following systems [7,8], and general systems [9,10]. In practice, it is very rare, that all agents in MAS have exactly the same dynamics.…”

“…Many researches are focused on the consensus problem of homogeneous MAS [1][2][3][4][5][6][7][8][9][10], but the output consensus problem of heterogeneous MAS is not common [11,13,15,16]. So the original method of dealing with homogeneous problems cannot be directly applied.…”