Learning-based control methods are an attractive approach for addressing performance and efficiency challenges in robotics and automation systems. One such technique that has found application in these domains is learning-based model predictive control (LBMPC). An important novelty of LBMPC lies in the fact that its robustness and stability properties are independent of the type of online learn...

In this paper we propose a vision-based stabilization and output tracking control method for a model helicopter. A novel two-camera method is introduced for estimating the full six-degrees-of-freedom pose of the helicopter. One of these cameras is located on-board the helicopter, and the other camera is located on the ground. Unlike previous work, these two cameras are set to see each other. Th...

Although periodicity simplifies design and analysis in control theory, it is no more adapted for embedded systems because it results in a conservative usage of resources. Indeed, the control signal is computed and updated at the same rate regardless whether is really required or not. On the other hand, event-driven sampling calls for resources whenever they are indeed necessary. Event-based PID...

The focus of this study is on the attitude estimation of the four-rotor helicopter known as quadrotor. The choice of the algorithm is a complementary filter based on quaternions. For the four-rotor helicopter system has nonlinear, strong coupling, multi-variable features, it is difficult to obtain the accurate attitude values, and in order to solve this problem a quaternion-based complementary ...

This article addresses the development and experimental validation of a trajectory-tracking control for miniature autonomous Quadrotor helicopter system (X4-prototype) using robust algorithm based on second-order sliding mode technique or also known as super-twisting in outdoor environments. nonlinear strategy guarantees convergence finite time to desired path r(t) presence external disturbance...