Jonatan Alvarez-Munoz

Cooperative aerial multi-robot systems (MRS) are increasingly being considered for missions in uncertain and dynamic environments, where reliable coordination must be maintained despite sensor failures, external disturbances, and limited onboard computational resources. However, achieving resilient coordination while simultaneously maintaining tracking accuracy and computational efficiency remains challenging. To address these challenges jointly, we develop a hybrid architecture that combines adaptive value tracking (AVT)-based coordination and multilateration for position reconstruction, an extended state observer (ESO) for real-time disturbance estimation and compensation, and event-triggered control (ETC) to reduce unnecessary actuator updates. Theoretical analysis based on Lyapunov stability guarantees the convergence of the estimation and control errors. Simulation and real-world experiments using DJI/Tello quadrotors in a robot operating system (ROS)-based environment demonstrate improved robustness and formation-tracking accuracy relative to conventional periodic control, reducing control update frequency by 30% during trajectory-tracking in simulation and up to 70% during static formation regulation in physical flight tests. The multilateration scheme enables position reconstruction under sensor losses, while the ESO effectively compensates for wind disturbances. Overall, the results demonstrate that the proposed framework enables resilient cooperative operation under sensing failures and environmental disturbances while reducing control-update requirements.

Nonlinearity and uncertainty are major features in control systems. In this context, the present work proposes to merge the brain emotional learning model with the benefits of robust event-driven control to handle uncertain nonlinear systems. The state-dependent unmodeled dynamics is estimated via the limbic system-inspired learning algorithm and added to the nominal control signal for compensation purposes. Furthermore, aiming at reducing data processing, and inherently, computational cost, the controller is triggered asynchronously driven by events function. Moreover, the closed-loop stability of the proposed control scheme is verified through the Lyapunov formalism, as well as the sampling admissibility to prevent the Zeno phenomena. The performance observed in the numerical results witnesses the effectiveness of the proposed control scheme.

The present paper investigates the consensus control of a Multi-Agent System (MAS) composed by Vertical Take-off and Landing (VTOL) rotorcrafts subject to aerodynamic disturbances. Initially, the attitude's VTOLs model based on quaternion formalism is detailed to subsequently derive the corresponding control law. Likewise, the MAS translational dynamics is extended to entail the airframe's aerodynamics. In order to achieve the consensus objective, a robust adaptive event-triggered sliding-mode control (SMC) is synthesized considering a leader-follower scheme guaranteeing Lyapunov's closed-loop stability and avoiding the Zeno behavior. Results from an extensive simulation stage witness the effectiveness of the proposed control scheme. The latter allows to fulfill the collective consensus and leader's trajectory tracking objectives in presence of unknown disturbances while keeping a reduced computational cost.

In the present work, an adaptive backstepping algorithm is developed in order to counteract the effects of disturbances. These disturbances are modeled as a constant force in the translational model part and as a constant torque in the orientation model part. We make the deduction of the mathematical expression for the proposed control algorithm and also we show its performance in simulation. Additionally, we include some experiments for validating the results obtained via simulation.

Event-triggered control is a resource-aware sampling strategy that updates the control value only when a certain condition is satisfied, which denotes event instants. Such a technique allows to reduce the control computational cost and communications. In this paper, a quaternion-based feedback is developed for event-triggered attitude stabilization of a quadrotor mini-helicopter. The feedback is derived from the universal formula for event-triggered stabilization of general nonlinear systems affine in the control. The proposed feedback ensures the asymptotic stability to the desired attitude. Real-time experiments are carried out in order to show the convergence of the quadrotor states to the desired attitude as well as the robustness with respect to external disturbances. Results show that the proposed control can reduce by 80 % the communications of the embedded system without sacrificing performance of the whole system. To the best of the authors' knowledge, this is the first time that a nonlinear event-triggered controller is experimentally applied to the attitude stabilization of an unmanned aircraft system.