Distributed tracking control of a class of multi-agent systems in non-affine pure-feedback form under a directed topology
Yang Yang, Dong Yue · IEEE/CAA Journal of Automatica Sinica · 2017
In this paper, we consider a consensus tracking problem of a class of networked multi-agent systems (MASs) in non-affine pure-feedback form under a directed topology. A distributed adaptive tracking consensus control scheme is constructed recursively by the backstepping method, graph theory, neural networks (NNs) and the dynamic surface control (DSC) approach. The key advantage of the proposed control strategy is that, by the DSC technique, it avoids “explosion of complexity” problem along with the increase of the degree of individual agents and thus the computational burden of the scheme can be drastically reduced. Moreover, there is no requirement for prior knowledge about system parameters of individual agents and uncertain dynamics by employing NNs approximation technology. We then further show that, in theory, the designed control policy guarantees the consensus errors to be cooperatively semi-globally uniformly ultimately bounded (CSUUB). Finally, two examples are presented to validate the effectiveness of the proposed control strategy.