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This article proposed a variable gain fast terminal sliding mode controller with an estimator of the uncertainty model for a piezo positioning stage system. The designed terminal sliding mode control has some advantages over the linear sliding mode control such as fast convergence and chattering reduction while maintains its robustness to the uncertainties. Next, an indirect technique is developed to enable the elimination of the singularity problem corresponding to initial terminal sliding mode control. In addition, a cerebellar model articulation controller is carried out to estimate the nonlinear dynamics of the piezo positioning stage. To deal with unknown bounds of uncertainties and disturbances, the proposed scheme consists of using online tuning control gains that ensure the establishment of a real terminal sliding mode in a finite time. Moreover, a fuzzy logic scheme is presented to smooth out the discontinuity part of the control signal, hence improve the control performance. Stability analysis of closed loop system is provided using the Lyapunov function method. Experiment results are presented to evaluate the effectiveness of the designed control approach.

This paper introduces an adaptive attitude control based on a backstepping control scheme for a quadrotor helicopter test bed. First, aerodynamics and motion equations are provided to model the dynamics of the quadrotor and a Virtual Reality (VR) model is developed incorporating the dynamic model to the virtual results of simulation. Then, an adaptive backstepping algorithm is applied to the attitude control and this algorithm is adaptive according to Lyapunov-based stability analysis. Finally, the simulation results with many types of reference signals are provided to demonstrate the good tracking performance of the proposed control algorithm.