Leader-Following Consensus Control for Multiple Fixed-Wing UAVs’ Attitude System With Time Delays and External Disturbances

Abstract

This paper proposes an algorithm of leader-following consensus control of multiple fixed-wing unmanned aerial vehicles'(UAVs) attitudes with time delays and unknown external disturbances. Firstly, a distributed controller based on undirected graph for leader-following consensus control of multi-UAVs' attitudes is proposed. Then, the effects of time delays are compensated with the help of Lyapunov-Krasovskii function, Cauchy and Young's inequality. Secondly, RBF neural network is introduced to estimate and reduce the negative effects of external disturbances. Finally, the effectiveness of the proposed distributed controller is demonstrated by Lyapunov theory and simulations. INDEX TERMS Leader-following consensus, multi-UAVs, time delays, unknown external disturbances, RBF neural network.

UAVs’ Formation Keeping Control Based on Multi–Agent System Consensus

“…From equations (24) and (26), direct calculation can get α 0 = 0.4551, τ 0 = 2.5132. Based on Theorem 1, the equilibrium (2, 0) of system (49) is locally stable when τ ∈ (0, τ 0 ) and undergoes a Hopf bifurcation when τ > τ 0 .…”

“…They proposed a model predictive control method for this cooperative positioning scheme to solve the problem of limited sensor perception space. In [24], Tang et al proposed an algorithm of leader-following consensus control of multiple fixed-wing UAVs' attitudes with time delays and unknown external disturbances. And a distributed controller based on undirected graph for leader-following consensus control of multi-UAVs' attitudes is proposed.…”

The Perturbations Estimation in Two Gas Plants

“…The perturbations estimation with fuzzy regulators is mentioned in [14] and [15]. In [16]- [18], and [19], the authors use the neuro-fuzzy approximations for the perturbed plants regulation. The adaptive laws for the perturbed plants regulation are focused in [20], [21], and [22].…”

“…The associate editor coordinating the review of this manuscript and approving it for publication was Ning Sun . [12], [13], [17], and [19], the authors use approaches for the variables or perturbations estimation in nonlinear plants; then it would be welcome to be focused on this issue. The novelty of this article is that each nonlinear plant has a different structure; consequently, a special estimator with the structure of the gas plants must be discussed.…”

“…There are various estimators who use the plant outlets for the variables estimation [1], [2], [5], [6], but there are not many estimators who use the plant outlets for the perturbations estimation. In [7], [8], [11], [13], [17], [19], previous studies of estimators are focused for the perturbations estimation, but with the two below differences: in the previous studies estimators with adaptive or feedback outlets are used, while in this article an estimator with sliding modes outlets is used, in the plants of previous studies the noise is not used, while in the plants of this article the noise is used.…”