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In this paper, we mainly investigate the finite-time consensus problem of general linear multi-agent systems. The paper proposed a suitable event-triggered control strategy. The strategy has some desirable properties including: distributed, independent, and asynchronous. It is theoretical demonstrated that the multi-agent system can achieve consensus in a certain time regardless of the initial condition under this event-triggered control scheme. In addition, without finding singular triggering problem, we prove the feasibility of this proposed event-triggered control protocol. Finally, we put forward some simulation graphs for the sake of showing the availability of our conclusions. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, the finite-time synchronization between two complex dynamical networks via the periodically intermittent adaptive control and the periodically intermittent feedback control is studied. The finite-time synchronization criteria are derived based on finite-time stability theory, the differential inequality and the analysis technique. Since the traditional synchronization criteria for some models are improved in the convergence time by using the novel periodically intermittent adaptive control and periodically intermittent feedback control, the results of this paper are important. Numerical examples are finally presented to illustrate the effectiveness and correctness of the theoretical results. [Copyright &y& Elsevier]

Abstract: This paper investigates the stabilization of three dimensional chaotic systems in a finite time by extending our previous method for chaos stabilization. Based on the finite-time stability theory, a control law is proposed to realize finite-time stabilization of three dimensional chaotic systems. In comparison with the previous methods, the controller obtained by our method is simpler than those. Moreover, the method obtained in this paper is suitable for a class of three dimensional chaotic systems. The efficiency of the control scheme is revealed by some illustrative simulations. [Copyright &y& Elsevier]

This paper considers the issues of both state estimation and unknown information reconstruction for a class of uncertain complex dynamical networks subject to unknown inputs. First, a robust adaptive sliding mode observer which can be used to estimate the states of complex networks through available measurement outputs is developed by employing both adaptive technique and sliding mode control approach. Second, a high-gain second-order sliding mode observer is considered to exactly estimate the derivatives of the output vectors in a finite time. Third, by using the estimates of the states and output derivatives, a kind of algebraic unknown input reconstruction method is proposed. Finally, some numerical simulation examples are given to illustrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]