The thermal conductivity of monolayer graphene nanoribbons (GNRs) with different tensile strain is investigated by using a nonequilibrium molecular dynamics method. Significant increasing amplitude of the molecular thermal vibration, molecular potential energy vibration and thermal conductivity vibration of stretching GNRs were detected. Some 20%~30% thermal conductivity decay is found in 9%~15% tensile strain of GNR cases. It is explained by the fact that GNR structural ridges scatter some low-frequency phonons which pass in the direction perpendicular to the direction of GNR stretching which was indicated by a phonon density of state investigation.

In this paper, an adaptive law with an integral action is designed and implemented on a DC motor by employing a rotary encoder and tachometer sensors. The stability is proved by using the Lyapunov function. The tracking errors asymptotically converge to zero according to the Barbalat lemma. The tracking performance is specified by a reference model, the convergence rate of Lyapunov function is specified by the matrix Q and the control action and the state weighting are restricted by the matrix . The experimental results demonstrate the effectiveness of the proposed control. The maximum errors of the position and velocity with the integral action are reduced from 0.4 V and 1.5 V to 0.2 V and 0.4 V, respectively. The adaptive control with the integral action gives satisfactory performance, even when it suffers from input disturbance.

This paper investigates the problems of reliable passivity and passification for a singular Markovian system with actuator failure. Using the Lyapunov approach, two sufficient conditions are given in terms of linear matrix inequalities (LMIs) such that a singular Markovian system is stochastically admissible and passive. Moreover, the existence of the established state-feedback controller is given in terms of strict LMIs. Finally, a numerical example is used to demonstrate the effectiveness of the given theoretical results.

The traditional aircraft controller design is usually based on the off-line aerodynamic model. Due to the deviation of the off-line aerodynamic model, the flight quality is difficult to meet the requirements when the aircraft is flying in the real atmosphere. To solve this problem, this paper proposes a frequency domain identification-based improved adaptive nonlinear dynamic inversion (NDI) control method (FDI-ANDI). In this paper, an online recursive aerodynamic parameter identification method in the frequency domain is first designed, and then an adaptive dynamic inversion control method based on the online aerodynamic parameter identification results is established. Finally, aiming at the problem of the slow response speed of the NDI controller, an improved adaptive dynamic inversion control law is designed by using the method of series lead correction. Compared with the traditional control method, the adaptive dynamic inversion method based on online aerodynamic identification has stronger robustness and a faster response speed in the face of model uncertainty. The final simulation analysis shows that the method has a better control effect than the traditional control method.