In this paper, a 6-Degrees-of-Freedom (6-DOF) Unmanned Aerial Vehicle (UAV) system with external disturbance corresponding to sensor failure is considered. The control method is presented in two parts. In the first part, the upper bound of external disturbance is known and a Proportional-Integral-Derivative (PID) Sliding Mode Control (SMC) technique is planned for maintaining the desired position in the finite time. Whereas, the upper bound of the external disturbance is considered unknown in the second part and the adaptive PID-SMC method is offered for stability and position tracking control of UAV systems. Using the Lyapunov stability notion, the offered control method proves that the quadrotor’s states can be tracked and stabilized in the finite time. Moreover, for the approximation of unknown bound of the external disturbances which are entered in the quadrotor dynamic model at any moment, adaptive control laws have been applied. Finally, simulation outcomes are provided to display the efficiency of the recommended technique.

Foreign Language Anxiety (FLA) is considered a central affective factor influencing English as a Foreign Language (EFL) learning. This study thus developed an online simulation game to create a virtually situated learning environment for reducing EFL primary school students’ FLA levels and improving their English vocabulary learning. A total of 110 fifth graders from four classes participated in this study. Two classes were randomly assigned to the experimental group (N = 57) using the online simulation game, and the other two classes were the control group (N = 53) using onsite instruction. Each participant was then classified as a low, moderate, or high anxiety student based on the Foreign Language Classroom Anxiety Scale (FLCAS). This study found that, compared to the onsite instruction, the online simulation game more effectively assisted the low, moderate, and high anxiety students in reducing their FLA. Situated learning in the online simulation game made a connection between English vocabulary learning and the real world explicitly and visibly, which could further promote their English vocabulary learning. In particular, the moderate and high anxiety students’ English vocabulary learning was significantly improved after the online simulation game. These results suggest that an online simulation game can create a situated learning environment that helps reduce EFL students’ FLA and subsequently facilitate their English vocabulary learning.

This paper designs and implements a robust and Time-varying Constrained Model Predictive Controller (TCMPC) for the translational and attitude control of a real quadrotor. The proposed approach considers online optimization to find solutions through the hard and soft constraints. All the controller parameters were derived from the experimental test setup and took into consideration the various restrictions and physical constraints associated with the hand-made quadrotor. The proposed controller can possibly linearize and discretize the nonlinear dynamic model of the quadrotor at every sampling time if all constraints and physical restrictions are considered. The performance of the proposed approach was assessed using both a simulation study and a practical implementation. The simulation study considered a quadrotor hovering mode in the presence of wind gusts and encompassed a comparison analysis with a well-tuned Proportional-Integral-Derivative (PID) controller, an Advanced Error model predictive control (AEMPC), and an Efficient MPC (EMPC) approach. For the real-time implementation, an online optimization algorithm was used and tested on the high clock processor ARM A53 on a new attitude test setup. The experimental results, showed that the proposed controller outperformed the unconstrained MPC, the well-tuned PID controller, and EMPC, especially in terms of rejecting the external wind disturbances. The proposed method real-time TCMPC) approach has the advantages of greater robustness and is not heavily dependent upon the accurate dynamics of the model.