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.
Highlights
Nowadays, the consensus problem for multi-agent systems (MASs) has been paid more and more attention owing to its great potential in various science and engineering areas
This paper aims to design a dead-zone compensator and fast finite-time consensus (FTC) protocol for system (1) in the presence of unknown dead-zone input, uncertainties and external disturbances, such that the fast FTC of system (1) can be achieved
Adaptive fast FTC and dead-zone compensator protocols will be designed for second-order MASs
Summary
The consensus problem for MASs has been paid more and more attention owing to its great potential in various science and engineering areas. Many distributed cooperative control problems, such as formation control, rendezvous, containment control, synchronization, flocking and so forth [1]–[5] have been widely studied in the presence of consensus schemes. An important problem on the cooperative control of MASs is that all the agents can reach an agreement by designing the control protocols, the agents could be robots, humans and so on. Convergence rate is of great significance for the consensus control of MASs owing to its enormous advantages. Asymptotic consensus relevant research results were presented in [6], [7], which means that convergence time was infinite.
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