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This paper addresses the distributed formation containment control problem of Euler–Lagrangian systems(ELSs) with unknown control directions by two layers, namely, time-varying formation for the leaders and containment formation control for the followers. We first estimate the desired states and velocities for the leaders and the followers in finite time. Second, novel adaptive neutral networks are used to compensate the model uncertainties. Third, using the Nussbaum gain technique, the proposed control laws can guarantee the ultimate convergence of error signals to zero and that all of the signals in the closed-loop system are bounded. Finally, simulation examples are given to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, the problem on an unique equilibrium solution of the bidirectional associative memory neural networks with distributed time-varying delays is investigated via Lyapunov stability theory. By using topological degree theory and M-matrix theory, several sufficient conditions ensuring the existence, uniqueness and global asymptotic stability of equilibrium solution are derived. An illustrative example is given to demonstrate the effectiveness of the obtained results. [Copyright &y& Elsevier]