This paper presents the design of a nonlinear optimal control strategy for a wind energy generation system based on a small scale wind turbine, a permanent magnet synchronous generator, a back-to-back power converter, and an LCL filter interconnected with the grid. The main control objectives in this energy system involve the trajectory tracking and regulation of different system variables as generator angular speed, DC-link voltage and reactive power. In order to fulfill these objectives, the application of optimal controllers based on the state-dependent coefficient factorization technique is proposed for both the generator-side converter and the grid-side converter. The advantages of the proposed control scheme are to achieve a wide system operating range, due to the controller design takes into account the system nonlinearities, and in addition, an efficient trajectory tracking of time-varying references generated by a maximum power point tracking algorithm, which uses a wind speed estimator. Also, an LCL filter is used to attenuate the harmonic content of the injected current to the utility grid to satisfy interconnection standards, which requires a THD below 5%. The effectiveness of the proposed controllers is verified via simulations developed in Matlab/Simulink, where the variables to be controlled reach the desired references that ensure proper operation, maximum power extraction, and fulfillment of interconnection standards.

This paper proposes the study of a robust control scheme for an Unmanned Surface Vehicle (USV) in a urban waterway using Visual Odometry (VO) for position estimation of the vehicle instead of traditional sensors. For different applications, a USV is required to operate in autonomous navigation mode and under various disturbances inherent to its environment as currents and waves. To achieve efficient operation, a robust control scheme is required to cope with such disturbances. The autonomous navigation is achieved by using VO to estimate the vehicle’s position for denied Global Positioning Systems (GPS) environments. A robust control scheme based on Sliding Modes (SM) control theory is designed and its convergence is guaranteed by means of Lyapunov analysis. The tracking capabilities under disturbance conditions using VO for position estimation are verified in simulation using the virtual world tool from Matlab and Simulink.

Photovoltaic (PV) systems are among the most used alternatives for electrical power generation from renewable sources. To ensure that PV systems make the most of the available solar energy, maximum power point tracking (MPPT) schemes must be implemented, which usually require voltage and current sensors to track the PV power. This paper presents the design of a robust observer using the Attractive Ellipsoid Method to achieve a precise estimation of PV current under parametric uncertainty and output perturbations. The application of such an observer enables the PV generation system to operate in a current sensorless mode, which reduces the overall cost of the system and enhances its reliability. The convergence of the observer is guaranteed by solving an optimization problem which generates the optimal gains using Linear Matrix Inequalities (LMI). To prove the effectiveness of the proposed sensorless scheme, simulations are performed in Matlab under test profiles based on the EN50530 standard and parameter uncertainty conditions, obtaining an accurate estimation which is used for MPPT operation.

La diabetes mellitus tipo 1 requiere de un estricto control en la administración de insulina para evitar consecuencias graves derivadas de la hiperglucemia y la hipoglucemia. El concepto de páncreas artificial permite la automatización en el tratamiento de pacientes con esta enfermedad, sin embargo, requiere de algoritmos de control capaces de operar eficientemente para mantener la concentración de glucosa en la sangre en niveles apropiados. Estos niveles apropiados en conjunto con el hecho de que el controlador no puede eliminar insulina del sistema nos indican que la salida y la entrada se encuentran acotadas, lo cual es considerado en el diseño del controlador para mejorar su desempeño. Debido a la presencia de incertidumbres y perturbaciones externas se propone el uso de un controlador robusto basado en un observador de estados extendidos generalizado (EGESO) que asegure una operación eficiente que evite episodios de hiperglucemia e hipoglucemia. Con el uso del EGESO se pueden estimar tanto los estados del sistema como las perturbaciones, lo cual elimina la necesidad de conocer información sobre las horas de ingesta, así como las cantidades a ingerir. La estabilidad del sistema de control propuesto es asegurada mediante el método del elipsoide atractivo y la solución de un problema de optimización basado en desigualdades matriciales bilineales (BMI). El desempeño del esquema de control propuesto es verificado mediante pruebas de simulación en Simulink, donde se observa que el controlador propuesto emula la terapia de bucleabierto en la cual el paciente debe administrar un bolo de insulina de forma paralela a cada ingesta.