The present paper proposes a Fast Terminal Sliding Mode Controller (FTSMC) for tracking uncooperative ground targets with a quadrotor UAV (QUAV). The method combines visual feedback information with onboard measurements to ensure accurate and reliable tracking. Simulation results reveal significant improvements in response time and minimal steady-state errors compared to the conventional first-order Sliding Mode Controller (SMC). These findings confirm the effectiveness of the FTSMC for dynamic and real-world applications, offering high precision, robustness, and fast convergence in finite time.

This work explores target interception with quadrotors, adapting missile guidance laws to aerial platform dynamics. A Line-of-Sight (LOS) guidance model, combined with an Active Disturbance Rejection Control (ADRC) system, addresses target maneuverability. The ADRC compensates for disturbances and motion variations, ensuring stable and precise interception. Simulations show the approach’s robustness and superior performance, highlighting its potential for autonomous aerial defense and interception in uncertain environments.

This paper presents the modeling and control of a tilt-birotor Unmanned Aerial Vehicle (UAV), an emerging aerial platform that combines efficiency and agility. Departing from conventional multirotor configurations, the birotor drone utilizes two tiltable rotors to generate lift and directional control. This not only reduces the drone’s weight but also allows better maneuverability, at the expense of higher nonlinearity and couplings in the drone model. To improve tracking performance and robustness an attitude and altitude stabilization strategy, based on a nonlinear backstepping controller, is proposed in this work. To generate the low-level control inputs, the proposed controller is combined with both linear and nonlinear allocation strategies. Simulation results, conducted on the full non-linear model of a V-shaped birotor design, confirm the viability of the proposed control strategy.

This paper deals with energy modeling and power consumption of new unconventional quadrotors according to the rotation angle of the arms, the angular velocity of rotors, and the path curvature changes. Thus, the main dynamic behaviors of the system influence the power consumption. For that, it is important to first understand its behavior, its environment, and its dynamics through dynamic modeling. Then, the implementation of control laws is necessary to ensure stability and good trajectory tracking. For that, an adaptive controller-based backstepping method is designed and applied to our system. The mathematical model of power consumption is formulated and the energy consumption is calculated. Finally, a comparison between different scenarios has been validated through simulation for different configuration and curvature values.

This paper presents a robust adaptive proportional-integral (PI) controller for permanent magnet synchronous generator (PMSG) based-wind turbine scheme to improve its low voltage ride-through (LVRT) capability at voltage sags. Concurrent control syntheses of rotor-side converter and grid-side converter are to regulate the DC-link voltage at voltage sags and resume it to its pre-fault condition. This PI adaptive control is designed via feedback linearization technique [5]; moreover, along with adaptation scheme, sliding mode surface is incorporated to guarantee robustness of the LVRT capability. Stability analysis of the closed-loop has been proven using Lyapunov-based analysis. Simulation results in Matlab demonstrate the proposed method.

In this paper, an intelligent PD (iPD) controller named Model-Free Controller is proposed. Herein, it is used to control the position of a Vertical Take-Off and Landing (VTOL) Unmanned Aerial Vehicle (UAV) Quadrotor. This strategy increases the control performance as well as its robustness level with respect to the classical PD. This is due to the estimation principle provided by the ultra-local model that estimate the unknown disturbances and uncertainties each iteration. The efficiency of the proposed strategy is shown through various numerical simulations where a thorough analysis is provided. Moreover, a comparison study is elaborated between the iPD and the classical PD.

In this paper, two redundant controllers are proposed in order to boost the capabilities of the popular feedback linearization flight controller scheme. The first one is based on the sliding mode framework whilst the second one is built upon the Model Free Control (MFC) theory. An in-depth discussion is highlighted with detailed evaluation in terms of performance, consumed energy, and robustness by considering several scenarios and using several metrics. The numerical simulations have shown satisfactory results using nominal system model or disturbed model through an application to a small Vertical Take-Off and Landing (VTOL) quadrotor.

International audience

In this paper, a quadrotor optimal coverage planning approach in damaged area is considered. The quadrotor is assumed to visit a set of reachable points following the shortest path while avoiding the no-fly zones. The problem is solved by using a two-scale proposed algorithm. In the first scale, an efficient tool for cluttered environments based on optimal Rapidly-exploring Random Trees (RRT) approach, called multi-RRT* Fixed Node (RRT*FN), is developed to define the shortest paths from each point to their neighbors. Using the pair-wise costs between points provided by the first-scale algorithm, in the second scale, the overall shortest path is obtained by solving the Traveling Salesman Problem (TSP) using Genetic Algorithms (GA). Taking into consideration the limited onboard energy, a second alternative based on the well-known Vehicle Routing Problem (VRP) is used. This latter is solved using the savings heuristic approach. The effectiveness of this proposed two-scale algorithm is demonstrated through numerical simulations and promising results are obtained.