In this paper, the design of a controller for the altitude and rotational dynamics is presented. In particular, the control problem is to maintain a desired altitude in a fixed position. The unmanned aerial vehicle dynamics are described by nonlinear equations, derived using the NewtonEuler approach. The control problem is solved imposing the stability of the error dynamics with respect to desired position and angular references. The performance and effectiveness of the proposed control are tested, first, via numerical simulations, using the Pixhawk Pilot Support Package simulator provided by Mathworks. Then, the controller is tested via a real-time implementation, using a quadrotor Aircraft F-450.

This paper presents a controller designed via the backstepping technique, for the tracking of a reference trajectory obtained via the photogrammetric technique. The dynamic equations used to represent the motion of the quadrotor helicopter are based on the Newton–Euler model. The resulting quadrotor model has been divided into four subsystems for the altitude, longitudinal, lateral, and yaw motions. A control input is designed for each subsystem. Furthermore, the photogrammetric technique has been used to obtain the reference trajectory to be tracked. The performance and effectiveness of the proposed nonlinear controllers have been tested via numerical simulations using the Pixhawk Pilot Support Package developed for Matlab/Simulink.

Despite the increasing use of unmanned aerial vehicles (UAVs) for pest control, there are still possibilities to optimize the spraying process by selecting the flight parameters of the operations involved, such as flight speed and height, according to the penetration of droplets that is sought to have in the corn plant. In this research, the flight parameters that the operators should select according to the type of disease they treat in corn crops were determined. To achieve this, first, a survey of the main diseases that attack corn crops in the region was carried out along with their location in the plant. Subsequently, flight tests were carried out selecting speeds of 2.80, 4.75, and 5.97 m/s and heights of 2.00, 2.75, and 3.50 m. The plants’ cover rates at the three different heights (top, middle, and bottom) were collected by hydrosensitive strips and scanned by the SnapCard scanning software. The use of statistical techniques allowed understanding the impact that flight parameters had on the coverage rate and droplet penetration: the higher the speed, the lower the coverage rate in the upper part of the plant and the higher the coverage rate in the lower part. On the other hand, the lower the height, the higher the coverage rate and droplet penetration.

The antilock braking system (ABS) is a mechatronic system that helps a driver maintain the maneuverability of a vehicle while braking by preventing wheel lock-ups. However, the design of high-performance controllers for this type of system is complicated because of its highly nonlinear dynamics. The problem becomes even more difficult to resolve when uncertainties in the parameters appear in its dynamics. In this paper, an ABS laboratory setup mimicking a quarter car model is considered. A modified high-order sliding mode (HOSM) controller using a proportional-integral-differential (PID) control as a sliding surface was designed. This controller provides a reference value of a tire slip. The proposed controller uses a tracking error to define the slip surface through the PID controller structure, and the modified HOSM controller holds the system on the previously designed slip surface. The closed-loop system stability has been proven in the sense of Lyapunov. Finally, the ABS laboratory setup allows for experimentally checking the performance of the modified HOSM controller using a PID-sliding surface, showing a considerable increase in the efficiency of the control system compared with a PID-like controller.

Unmanned Aerial Vehicles (UAVs) have become increasingly prevalent in various applications, ranging from surveillance to package delivery. Achieving precise control of UAV position while enhancing robustness against uncertainties and disturbances remains a critical challenge. In this study, we propose a robust nonlinear control system for a UAV and its actuators, focusing on accurately controlling the position reference vector and improving robustness against parameter uncertainties and external disturbances. The control strategy employs two control loops: an outer loop for the UAV frame and an inner loop for the UAV actuators. The outer loop generates the required angular velocities for the actuators to follow the reference position vector using the UAV’s output and the inner loop ensures that the actuators track these angular velocity references. Both control loops utilize PI-like controllers for simplicity. The proposed system incorporates nonlinear control techniques and estimation strategies for disturbances and parameter variations, enabling dynamic adaptation to changing environmental conditions. Numerical simulations were performed using both Simulink^® and the simulated PX4 Autopilot environment, showing the effectiveness of the proposed control system in achieving precise position control and robust performance for both the UAV and its actuators in the presence of uncertainties and disturbances. These results underscore the potential applicability of the control system in other UAV operational scenarios.

This study considers the design of a modified high-order sliding mode (HOSM) controller using a PI sliding surface to the attitude control of a ground vehicle. A robust-modified HOSM controller is derived, so that the lateral velocity and yaw rate tracks the desired trajectory despite the environment actions acting on the ground vehicle and parameter variations. The stability is guaranteed with Lyapunovs stability theorem function. The performance of the dynamic controllers is evaluated using the CarSim simulator considering a challenging double steer maneuver.