This work focuses on the design and construction of an experimental test bench of three degrees of freedom with application in educational environments. It is constituted by a gyroscopic structure that allows the movements of a quadcopter to analyze the control systems. In this context, the main features of the mechanical and electronic design of this prototype are described. At the same time, the main characteristics with respect to existing platforms are highlighted in aspects such as: system autonomy, cost, safety level, operation ranges, experimental flexibility, among others. The possible controller design approaches for quadcopter stabilization can extend to many basic and advanced techniques. In this work, to show the operation and didactic use of the platform, the development of the controller for tilt angle stabilization under two different approaches are presented. The first approach is through PID control, oriented for undergraduate students with basic level in control theory. The second approach is by means of State Feedback, oriented to students with more advanced level in this field. The result of this work is an open test bench, enabled for the experimentation of control algorithms using Matlab-Simulink.

The current environmental challenges require the implementation of environmentally friendly energy production systems. In this context, proton exchange membrane fuel cell stacks (PEMFC) represent, due to their high electrical efficiency and their low level of $CO_{2}$ emissions, a promising alternative technology. However, there are still many technical aspects that need to be improved before they become a commercial reality. One of them is the temperature control of the stack, since its electrical efficiency and its lifetime depend on the performance of this control. In this work, we design a multiloop PID control of the temperature of a PEMFC stack and validate it experimentally. The stack is the prime mover of a micro combined heat and power system (micro-CHP). For this task, we use a previously developed nonlinear model and apply a multiobjective optimization methodology. To assess its performance, the PID control is compared to a second PID control designed with a linearized model. The results show, on the one hand, the importance of having a nonlinear model valid in a wide operation range for the correct design of the temperature control of a PEMFC stack and, on the other hand, the advantages of applying a multiobjective optimization methodology to this problem.

A relevant task in unmanned aerial vehicles (UAV) flight is path planning in $3D$ environments. This task must be completed using the least possible computing time. The aim of this article is to combine methodologies to optimise the task in time and offer a complete $3D$ trajectory. The flight environment will be considered as a $3D$ adaptive discrete mesh, where grids are created with minimal refinement in the search for collision-free spaces. The proposed path planning algorithm for UAV saves computational time and memory resources compared with classical techniques. With the construction of the discrete meshing, a cost response methodology is applied as a discrete deterministic finite automaton (DDFA). A set of optimal partial responses, calculated recursively, indicates the collision-free spaces in the final path for the UAV flight.

This paper gathers the design and implementation of the control system that allows an unmanned Flying-wing to perform a Vertical Take-Off and Landing (VTOL) maneuver using two tilting rotors (Bi-Rotor). Unmanned Aerial Vehicles (UAVs) operating in this configuration are also categorized as Hybrid UAVs due to their ability of having a dual flight envelope: hovering like a multi-rotor and cruising like a traditional fixed-wing, providing the opportunity of facing complex missions in which these two different dynamics are required. This work exhibits the Bi-Rotor nonlinear dynamics, the attitude tracking controller design and also, the results obtained through Hardware-In-the-Loop (HIL) simulation and experimental studies that ensure the controller’s efficiency in hovering operation.

Micro-combined heat and power systems (μ-CHP) based on proton exchange membrane fuel cell stacks (PEMFC) are capable of supplying electricity and heat for the residential housing sector with a high energy efficiency and a low level of CO ₂ emissions. For this reason, they are regarded as a promising technology for coping with the current environmental challenges. In these systems, the temperature control of the stack is crucial, since it has a direct impact on its durability and electrical efficiency. In order to design a good temperature control, however, a dynamic model of the μ-CHP cooling system is required. In this paper, we present a model of the cooling system of a PEMFC-based μ-CHP system, which is oriented to the design of the temperature control of the stack. The model has been developed from a μ-CHP system located in the laboratory of our research team, the predictive control and heuristic optimization group (CPOH). It is based on first principles, dynamic, non-linear, and has been validated against the experimental data. The model is implemented in Matlab/Simulink and the adjustment of its parameters was carried out using evolutionary optimization techniques. The methodology followed to obtain it is also described in detail. Both the model and the test data used for its adjustment and validation are accessible to anyone who wants to consult them. The results show that the model is able to faithfully represent the dynamics of the μ-CHP cooling system, so it is appropriate for the design of the stack temperature control.

Demand for 3D planning and guidance algorithms is increasing due, in part, to the increase in unmanned vehicle-based applications. Traditionally, two-dimensional (2D) trajectory planning algorithms address the problem by using the approach of maintaining a constant altitude. Addressing the problem of path planning in a three-dimensional (3D) space implies more complex scenarios where maintaining altitude is not a valid approach. The work presented here implements an architecture for the generation of 3D flight paths for fixed-wing unmanned aerial vehicles (UAVs). The aim is to determine the feasible flight path by minimizing the turning effort, starting from a set of control points in 3D space, including the initial and final point. The trajectory generated takes into account the rotation and elevation constraints of the UAV. From the defined control points and the movement constraints of the UAV, a path is generated that combines the union of the control points by means of a set of rectilinear segments and spherical curves. However, this design methodology means that the problem does not have a single solution; in other words, there are infinite solutions for the generation of the final path. For this reason, a multiobjective optimization problem (MOP) is proposed with the aim of independently maximizing each of the turning radii of the path. Finally, to produce a complete results visualization of the MOP and the final 3D trajectory, the architecture was implemented in a simulation with Matlab/Simulink/flightGear.