The Unmanned Aerial Vehicle (UAV) attitude stabilization problem has been dealt with in many previous works through applying a vast range of philosophies of control strategies. In this paper, a discrete controller based on a Linear Quadratic Regulator (LQR) plus integral action is synthesized to stabilize the attitude and altitude of a quadrotor helicopter. This kind of control strategy allows us to reduce the energy consumption rate, and the desired UAV behavior is properly achieved. Experimental tests are conducted with external disturbances such as crosswinds deliberately added to affect the performance of the aerial vehicle. This provides experimental evidence that the integral part considered in the proposed control strategy contributes to improving the performance of the vehicle under external disturbances. In fact, a comparative analysis of potential and kinetic energy consumption is developed between the Optimal Integral Controller (OIC) and a Proportional Integral Derivative Controller (PID), allowing us to determine the level of improvement of the closed-loop system when the discrete Integral Optimal Controller is applied.

In this paper, a robust control technique is developed to achieve the quadrotor stabilization against unmodeled matching vanishing dynamics. The synthesis of the proposed robust control is based on the Lyapunov approach and the backstepping method allowing to construct an iterative control algorithm. To compare the performance of the proposed controller, a Proportional Derivative (PD) controller is used to obtain experimental results in an outdoor environment. To compare the closed-loop system responses with both controllers, the Integral Absolute Error is computed and several tests are conducted to calculate the error standard deviation. Ultimately, employing the robust backstepping control approach in pest recognition in maize crops, which is a specific task of precision agriculture, demonstrates its effectiveness in improving the trajectory tracking of the vehicle while it captures images of the crops.

This paper presents a discrete-time robust linear control method for tracking a hexacopter's trajectory in the presence of external disturbances. The control of multi-rotor type unmanned aerial vehicles (UAVs) has gained considerable attention recently due to their various applications, such as crop spraying in precision agriculture. The control of UAVs requires robustness to reject disturbances and accommodate dynamic uncertainties. To achieve this goal, the robust discrete-time control action is designed in two stages. The first stage utilizes the solution of a difference Riccati-equation to guarantee system stability in an optimal sense. The second stage provides system robustness against external disturbances and uncertain dynamics. Furthermore, the Lyapunov stability theory for discrete linear systems is used to derive system asymptotic stability. Finally, experimental results of the hexacopter flight are provided to illustrate the effectiveness of the presented control law.

A case study of a pharmaceutical distribution company with a relational database that is migrated to a document-oriented NoSQL database for which a hybrid distribution strategy based on fragmentation and replication is implemented. The legacy relational database schema was thoroughly analyzed and evaluated to determine the collections and documents needed to move all the data and leverage the capabilities of the document-based database. In addition, a hybrid data distribution strategy was designed to effectively balance the performance, scalability, and fault tolerance of the system. Finally, integrated operational tests were performed on the distributed system nodes to verify that they function properly and ensure their availability for the company's operations.

This article presents a suboptimal nonlinear control strategy to improve the dynamics of a three-phase alternating current (AC) motor. Using dynamic programming, the calculation of the Bellman function is avoided by determining a suboptimal control sequence that locally minimizes a quadratic performance index at each step. The motor’s fixed-frame nonlinear mathematical model controls the stator currents, rotor magnetic fluxes, and rotor angular speed by applying voltages to the stator. Experimental tests are conducted using a Delta VFD007EL11A variable frequency drive (VFD), demonstrating improved motor state behavior and performance compared to an optimal proportional integral (PI) control and a fixed reference input in the VFD. The experiments include set point changes and a comparative analysis of the energy consumption between both controllers considering two cases: free and with load on the motor shaft.