Este artículo presenta un controlador Fuzzy-PD para resolver el problema de seguimiento de pared a través de un robot móvil. El desempeño del controlador propuesto es comparado con un controlador clásico PD a través del análisis del índice de la integral del error cuadrático (ISE) y el índice de variación total de la acción de control (TV). Para el diseño del controlador Fuzzy-PD, se consideró la distancia que existe entre el robot móvil y la pared la cual es medida a través de un sensor ultrasónico que tiene el robot. En este trabajo se realizaron dos pruebas con el objetivo de mostrar la efectividad que posee cada controlador; un cambio de referencia de la distancia de seguimiento y el seguimiento de una pared desconocida. Los controladores fueron sintonizados a través del algoritmo de optimización por enjambre de partículas (PSO) e implementados en la plataforma DaNI 2.0 mediante el uso del software LabView Robotics.

This paper presents a comparative experimental evaluation of three control strategies for angular position regulation of a Vertical Take-Off and Landing (VTOL) system: a conventional Proportional–Integral–Derivative (PID) controller, a Linear Quadratic Integral (LQI) controller, and a proposed nonlinear PID (NL-PID) controller. The proposed strategy extends the conventional PID structure by introducing a nonlinear gain that dynamically modulates the control action according to the evolution of the tracking error. The controller gains of the nonlinear PID are obtained through a genetic algorithm optimization process based on the Integral of the Squared Error (ISE) and maximum overshoot. Experimental evaluation is performed through three tests under different operating conditions: a normal test, an uncertain physical parameter test, and an external perturbation test. The angular position response and control effort of the three controllers are analyzed, with tracking performance quantitatively evaluated using the Integral of the Squared Error (ISE), Integral of the Absolute Error (IAE), and percentage overshoot (PO). The results show that the proposed NL-PID consistently provides the best tracking performance among the evaluated controllers. In the normal test, the NL-PID achieves the lowest ISE and IAE, with reductions in ISE of 16.34% and 7.25% compared with the conventional PID and LQI controllers, respectively. Under an uncertain physical parameter, these reductions increase to 19.89% and 7.54%, respectively, while the NL-PID also exhibits the lowest IAE and percentage overshoot. Under an external perturbation, the NL-PID achieves the lowest ISE and IAE, reducing the accumulated squared and absolute tracking errors by 12.06% and 15.65% compared with the PID controller, and by 22.50% and 35.29% compared with the LQI controller, respectively. These results demonstrate the potential of the proposed nonlinear PID to improve angular position tracking performance under different operating conditions while preserving the simplicity of the conventional PID structure.

Solar and wind variability can limit renewable generation under contrasting regional conditions. This study evaluates a solar–wind–biomass hybrid system for Puerto Quito, Valencia, and Tena, Ecuador, using MATLAB/Simulink R2024b with NASA POWER meteorological inputs, PVGIS as a complementary solar reference, and biomass assumptions informed by the Ecuadorian Bioenergy Atlas. Under a controlled biomass scenario of 1500 t/year, the biomass subsystem supplied 87.7 kW. Mean hybrid outputs were 137, 130, and 128 kW, equivalent to 1200.1, 1138.8, and 1121.3 MWh/year, respectively. Adding the common biomass contribution reduced the relative regional spread from 22.3% to 7.0%, while the absolute Puerto Quito–Tena difference remained 9 kW. Biomass sensitivity and analytical uncertainty screening further characterized the influence of resource and model assumptions on the comparative results.