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This paper addresses the distributed leader‐following consensus control of second‐order strict‐feedback nonlinear multi‐agent systems. By employing mean value theorem, variable separation technique, and backstepping methodology, a fully distributed adaptive control law is designed using only local relative state information. The proposed control law solves the leader‐following consensus problem for any directed communication graph that contains a spanning tree with the root node being the leader agent. The application to hovercraft slew rate control system is given to verify the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper deals with the robust consensus tracking problem for a class of heterogeneous second-order nonlinear multi-agent systems with bounded external disturbances. First, a distributed adaptive control law is proposed based on the relative position and velocity information. It is shown that for any connected undirected communication graph, the proposed control law solves the robust consensus tracking problem. Then, by introducing a novel distributed observer and employing backstepping design techniques, a distributed adaptive control law is constructed based only on the relative position information. Compared with the existing results, the proposed adaptive consensus protocols are in a distributed fashion, and the nonlinear functions are not required to satisfy any globally Lipschitz or Lipschitz-like condition. Numerical examples are given to verify our proposed protocols. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper is about solving the output regulation problem for a class of infinite dimensional systems with an unknown exosystem. First, under the unit relative degree assumption, the infinite dimensional system is decomposed into a cascaded one composed of a one-dimensional system and an infinite dimensional system. Then, the problem is solved by combining an adaptive internal model and an adaptive control. The presented results are illustrated via a periodic tracking problem of a heat equation. [ABSTRACT FROM AUTHOR]

This study addresses the output‐feedback control problem for a class of Markovian jump non‐linear systems under a quadratic risk‐sensitive cost function criterion. The transition probabilities of the Markov process are assumed to be completely unknown. By employing the high‐gain scaling technique, common Lyapunov function method and backstepping technique, a control law is constructed that guarantees any arbitrary small risk‐sensitive cost for a given risk‐sensitive parameter. Moreover, the resulted closed‐loop system solutions are bounded in probability. Compared with some previous results, this study does not require the uniform boundedness of the gain functions of the system noise, and the control law further achieves a zero risk‐sensitive cost and asymptotically stable in the large for the closed‐loop system solutions when the vector field of the disturbance vanishes at the origin. A numerical example is given to illustrate the proposed protocol. [ABSTRACT FROM AUTHOR]