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In this paper, we study the cooperative global robust output regulation problem for nonlinear multiagent systems in output feedback form with any relative degree subject to directed switching networks. Through the augmentation by a distributed internal model and a distributed observer of the given system, we first convert the original problem into the global robust stabilization problem of the so-called extended augmented system, which is a multi-input-coupled switched system. Then, we establish a few technical lemmas to lay the foundation for constructing a switching control law and the corresponding multiple Lyapunov functions for the switched system. Then, we present the solvability conditions of our problem via the multiple Lyapunov functions and average dwell time method. The main result will be applied to the leader-following synchronization problem for a group of hyperchaotic Lorenz multiagent systems with a directed switching network. [ABSTRACT FROM PUBLISHER]

This technical note studies the cooperative global robust output regulation problem for a class of nonlinear multi-agent systems with switching network by a distributed output feedback control law. We first convert the problem via the internal model approach to a global robust stabilization problem of an augmented system. Then, using average dwell time method, we present a set of solvability conditions for the latter problem by a distributed switched output feedback control law, thus leading to the solution of the original problem. Our approach is illustrated by a family of Lorenz systems subject to a harmonic exosystem. [ABSTRACT FROM AUTHOR]

In this technical note, we study the global disturbance rejection problem of nonlinear systems in lower triangular form with unknown exosystem via state feedback control. The problem is dealt with in two steps. In the first step, an augmented system composed of the given plant and an internal model is constructed. Owing to the presence of the unknown parameter in the exosystem, the augmented system contains both nonlinearly and linearly parameterized uncertainties. In the second step, the stabilization of the augmented system is solved by an approach integrating both robust and adaptive techniques. The solution of the stabilization problem of the augmented system in turn leads to the solution of the global disturbance rejection problem of the original system. Further, the convergence issue of an estimated unknown parameter vector is also discussed. [ABSTRACT FROM PUBLISHER]