Currently, a major obstacle faced by multirotor unmanned aerial vehicles (UAVs) is the limitation of embedded energy. The research community has been exploring this issue through the analysis of design, control, and planning methods. Most of these strategies rely on comprehending the interrelated sub-dynamics of the DAV system, encompassing factors like propeller aerodynamics, electro-mechanical dynamics of the motor, and battery dynamic. This paper proposes an estimation algorithm based on a power consumption multiphysical model, which involves all these components and their coupling. Initially, we build sub-models for each component dynamics and then incorporate them to draw up a multiphysical model that can predict with some degree of precision the consumed power during the UAV flight operation.

The study of control techniques for exoskeleton robots used in upper-extremity rehabilitation is gaining popularity. These robots are connected to the human upper limb at multiple points, allowing for smooth and independent joint movements. Therefore, providing a robust, precise, and safe control system is necessary. Sliding control-based approaches are well reputed for their robustness to parameter uncertainties, modeling errors, and external disturbances. Nevertheless, their major disadvantage is chattering. This paper describes two controllers based on sliding mode theory to reduce this undesirable effect: the generalized variable structure control and the higher-order finite-time sliding mode control. The former incorporates the derivative of the torque input in the model, while the latter is based on homogeneity and higher-order sliding modes to diminish chattering. A comparison between the two controllers is achieved by simulating passive rehabilitation mode.

A homogeneous continuous sliding mode control scheme based on finite time stability is developed in this paper for an upper limb exoskeleton robot dedicated for rehabilitation. Indeed this type of robot interacts directly with human limbs whose dynamics are unknown and different for users. Therefore, the main idea is to provide a robust motion control of the exoskeleton robot using a continuous higher order sliding mode controller despite parameters variations, uncertainties and external disturbances. The proposed controller combines the homogeneity concept and the super-twisting algorithm. Finite time stabilization is achieved using the first part of the controller while disturbance rejection is granted by the second part of the controller. Performance of the controller and its robustness are illustrated through simulations of trajectory tracking tests corresponding to passive rehabilitation exercises.