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This paper studies a consensus problem for a kind of stochastic multi-agent systems (SMAS). First, a reduced-order observer is designed to estimate unknown states in SMASs. Second, an event-triggered adaptive output feedback control method is presented. It can reduce the controller updates and communication burden. Moreover, the radial basis function neural networks are applied to approximate the unknown functions in systems. Finally, it is demonstrated that the proposed control scheme can achieve finite-time practical consensus for SMASs. Simulation results are provided to illustrate the effectiveness of the theoretical analysis.

This paper focuses on the study of fractional order terminal sliding mode control for nonlinear aerospace systems. Firstly, a novel fractional order integral terminal sliding mode control (FO-I-TSMC) method is proposed for the control of first order nonlinear system. FO-I-TSMC has three attractive advantages: i) Non-singular control law; ii) Elimination of the reaching phase; iii) Calculable finite convergence time. Furthermore, theory analysis is presented to reveal the potential advantages of the FO-I-TSMC method over its integer order counterparts. Secondly, a novel fractional order derivative integral-TSMC (FO-DI-TSMC) method is presented to deal with second order nonlinear system. Finally, FO-DI-TSMC is extended to deal with a general class of higher order control system. Simulation results are given to verify the effectiveness of the proposed methods.

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