Enrique Santiso

Three robotic platforms designed to serve as an entry point to mobile robotics are presented. One platform (Alcabot Electrical) is oriented for elementary or early high school students with a robot telecontrolled by electromechanical elements, without a microprocessor. A second platform (TuBot) based on Arduino is oriented to serve as an entry point in high school with certain limitations of functionality. The third platform (Alcabot Starting) is also based on Arduino but with components that make it very versatile, with many possibilities for expansion and oriented to secondary education, high school or even as an entry point for university students. All three platforms are designed with components easily available on the internet, low cost and with online support documentation for both hardware and software. All three platforms have been used with students and in teacher training courses with very good acceptance. The Alcabot Electrical and Alcabot Starting platforms have been designed as an entry point for the Eurobot and Eurobot Junior competitions to introduce children and young people to robotics and then modify, complement or use their components in their own designs adapted to the competition problem.

In rail transport, various automatic protection systems are available to ensure the safe operation of trains and to facilitate automation and optimization tasks. For this purpose, a set of physical balises is used, which are placed at fixed points along the railway track. Based on the information provided by these balises, different information is displayed to the driver, and control actions are generated. The use of physical balises located at fixed points does not allow for automatic protection actions on sections of track where they are not installed. This is a major drawback as in many cases, temporary automatic protection actions are necessary on sections of the railway line without balises due to various circumstances (work on the track, accidents, etc.). To solve this problem, this paper presents a solution called announcement signals and automatic braking using virtual balises (ASAB-VB). This proposal allows the incorporation of virtual balises at points on the track where it is necessary to temporarily perform automatic protection actions. For this purpose, the ASAB-VB system allows obtaining the train position in real-time and storing a digital map of the track that will be made by each train. This digital map includes geographic information about the balises (both physical and virtual ones) located on the track. At the same time, the train position is obtained by merging the information provided by a GNSS, an odometer, and an inertial system (gyro and accelerometers).

This paper describes a practical approach to the transformation of Base Transceiver Stations (BTSs) into scalable and controllable DC Microgrids in which an energy management system (EMS) is developed to maximize the economic benefit. The EMS strategy focuses on efficiently managing a Battery Energy Storage System (BESS) along with photovoltaic (PV) energy generation, and non-critical load-shedding. The EMS collects data such as real-time energy consumption and generation, and environmental parameters such as temperature, wind speed and irradiance, using a smart sensing strategy whereby measurements can be recorded and computing can be performed both locally and in the cloud. Within the Spanish electricity market and applying a two-tariff pricing, annual savings per installed battery power of 16.8 euros/kW are achieved. The system has the advantage that it can be applied to both new and existing installations, providing a two-way connection to the electricity grid, PV generation, smart measurement systems and the necessary management software. All these functions are integrated in a flexible and low cost HW/SW architecture. Finally, the whole system is validated through real tests carried out on a pilot plant and under different weather conditions.

Encouraged by the considerable cost reduction, small-scale solar power deployment has become a reality during the last decade. However, grid integration of small-scale photovoltaic (PV) solar systems still remains unresolved. High penetration of Renewable Energy Sources (RESs) results in technical challenges for grid operators. To address this, Virtual Power Plants (VPPs) have been defined and developed to manage distributed energy resources with the aim of facilitating the integration of RESs. This paper introduces a hybrid irradiance forecasting approach aimed at facilitating the integration of PV systems into a VPP, especially when a historical irradiance dataset is exiguous or non-existent. This approach is based on Artificial Neural Networks (ANNs) and a novel similar hour-based selection algorithm, has been tested for a real PV installation, and has been validated also considering irradiance measurements from an aggregation of ground-based meteorological stations, which emulate the nodes of a VPP. Under a reduced historical dataset, the results show that the proposed similar hour-based method produces the best forecasts with regard to those obtained by the ANN-based approach. This is particularly true for one-month and two-month datasets minimizing the mean error by 16.32% and 9.07% respectively. Finally, to demonstrate the potential of the proposed approach, a comparative analysis has been carried out between the hybrid method and the most used benchmarks in the literature, namely, the persistence method and the method based on similar days. It has been demonstrated conclusively that the proposed model yields promising results regardless the length of the historical dataset.

Condition monitoring of high voltage power lines through self-powered sensor systems has become a priority for utilities with the aim of detecting potential problems, enhancing reliability of the power transmission and distribution networks and mitigating the adverse impact of faults. Energy harvesting from the magnetic field generated by the alternating current flowing through high voltage lines can supply the monitoring systems with the required power to operate without relying on hard-wiring or battery-based approaches. However, developing an energy harvester, which scavenges the power from such a limited source of energy, requires detailed design considerations, which may not result in a technically and economically optimal solution. This paper presents an innovative simulation-based strategy to characterize an inductive electromagnetic energy harvester and the power conditioning system. Performance requirements in terms of the harvested power and output voltage range, or level of magnetic core saturation can be imposed. Different harvester configurations, which satisfy the requirements, have been produced by the simulation models. The accuracy and efficiency of this approach is verified with an experimental setup based on an energy harvester, which consists of a Si-steel magnetic core and a power conditioning unit. For the worst-case scenario with a primary current of 5 A, the maximum power extracted by the harvester can be as close as 165 mW, resulting in a power density of 2.79 mW/cm³.

This paper describes the theoretical and practical foundations for remote control of a mobile robot for nonlinear trajectory tracking using an external localisation sensor. It constitutes a classical networked control system, whereby event-based techniques for both control and state estimation contribute to efficient use of communications and reduce sensor activity. Measurement requests are dictated by an event-based state estimator by setting an upper bound to the estimation error covariance matrix. The rest of the time, state prediction is carried out with the Unscented transformation. This prediction method makes it possible to select the appropriate instants at which to perform actuations on the robot so that guidance performance does not degrade below a certain threshold. Ultimately, we obtained a combined event-based control and estimation solution that drastically reduces communication accesses. The magnitude of this reduction is set according to the tracking error margin of a P3-DX robot following a nonlinear trajectory, remotely controlled with a mini PC and whose pose is detected by a camera sensor.

Chalcographic printer is the name given to a specific type of press which is used to transfer the printing of a metal-based engraved plate onto paper. The printing system consists of two rollers for pressing and carrying a metal plate onto which an engraved inked plate is placed. When the driving mechanism is operated, the pressure exerted by the rollers, also called contact pressure, allows the engraved image to be transferred into paper, thereby obtaining the final image. With the aim of ensuring the quality of the result, in terms of good and even transfer of ink, the contact pressure must be uniform. Nowadays, the strategies utilized to measure the pressure are implemented off-line, i.e., when the press machines are shut down for maintenance, which poses limitations. This paper proposes a novel sensor system aimed at monitoring the pressure exerted by the rollers on the engraved plate while chalcographic printer is operating, i.e., on-line. The purpose is two-fold: firstly, real-time monitoring reduces the number of breakdown repairs required, reduces machine downtime and reduces the number of low-quality engravings, which increases productivity and revenues; and secondly, the on-line monitoring and register of the process parameters allows the printing process to be reproducible even with changes in the environmental conditions or other factors such as the wear of the parts that constitute the mechanical system and a change in the dimensions of the printing materials. The proposed system consists of a strain gauge-based load cell and conditioning electronics to sense and treat the signals.

This paper presents a simplified triggering mechanism for event-triggered control systems. The novelty of our work resides in the use of a triggering condition that only updates the controller when the time derivative of the Lyapunov function becomes non-negative, without taking into account the measurement error. Directly or indirectly, most previous works use the measurement error in the triggering condition, usually defining this error as the difference between the states of the plant under continuous and aperiodic implementation. The main idea of our proposal is to force the system to maintain the last control update whenever it is approaching the equilibrium point. To demonstrate the advantages of our triggering condition, we compare it with other control alternatives using the double integrator problem as a case study.