An adaptive robust controller for nonlinear and coupling dynamic of aerial vehicle has been presented. In this paper an adaptive sliding mode controller (ASMC) is integrated to design the attitude control for the inner loops of nonlinear coupling dynamic of Unmanned Aerial Vehicle (UAV) in the presence of parametric uncertainties and disturbances. In the proposed scheme, the adaptation laws can estimate the unknown uncertain parameters and external disturbances, while the sliding mode control is used to ensure the fast response and robustify the control design against unmodeled dynamics with a small control effort.The synthesis of the adaptation laws is based on the positivity and Lyapunov design principle. In comparison with other sliding mode approaches, the approach does not need the upper bound of parametric uncertainty and disturbances. The navigation outer loops of small UAV instead is based on PIDs to control altitude and heading. Simulation results demonstrate that the proposed controller can stabilize the nonlinear system and also it has stronger robustness with respect to the model uncertainties and gust disturbance. تفاصيل المقالة

In this research study, one of the most crucial automotive engineering problems is intended to be solved. The necessity of tire pressure monitoring system is beyond doubt. Such systems are now provided relying on expensive sensors. In this study an indirect tire pressure monitoring system is proposed, utilizing identification techniques, which will reduce the cost of monitoring considerably in comparison to direct types, while keeping it just as reliable as the conventional types. A comprehensive study on system’s parameters was undertaken by MATLAB-IDENTIFICATION toolbox, in order to find a proper method to estimate tire pressure indirectly. The best method was chosen among five well-known estimation methods, including Space State, AR, ARMA, NLARX and Wiener-Hammerstein. It was shown, the best method to estimate the pressure of a properly inflated tire is NLARX with a 94.51% precision while the best estimation for an under-inflated tire pressure is ARMA with a 92.3% accuracy. تفاصيل المقالة