Abstract
In this paper it is described a new Servo Motor Optimised for Educational Robotic Applications (SMORA), which comprises several sensors and higher level addressing/communication capabilities. Even though servos have excellent qualities when used in the field of robotics, several properties can still be enhanced. These devices are known to have nonlinear properties and dynamic factors such as dead-zones, backlash and friction that might hinder their precision and accuracy. They usually do not provide position, velocity or current feedback to the device controlling them. Factors such as change in the load attached to the system increase the complexity of the analysis even further. Controlling these servos using a PWM signal might also become complicated if the number of servo motors to control increases. The new proposed servo consists of custom hardware and firmware that includes a microcontroller and a series of sensors, allowing for the motor current, temperature and voltage to be measured in real-time as well as precise position feedback thanks to the integrated hall-effect magnetic position encoder. It also incorporates an accelerometer and a gyroscope to measure the servo body relative position and rotation.

Abstract
This paper addresses the problem of finding the best Brain Emotional Learning (BEL) controller parameters in order to improve the response of a single degree-of-freedom (SDOF) structural system under an earthquake excitation. The control paradigm considered is based on a semi-active system to control the dynamics of a lumped mass-damper-spring model, being carried out by changing the damping force of a magneto-rheological (MR) damper. A typical BEL based controller requires the definition of several parameters which can be proved difficult and non-intuitive to obtain. For this reason, an evolutionary based search technique has been added to the current problem framework in order to automate the controller design. In particular, the particle swarm optimization (PSO) method was chosen as the evolutionary based technique to be integrated within the current control paradigm. The obtained results suggest that, indeed, it is possible to parametrize a BEL controller using an evolutionary based algorithm. Moreover, simulation shows that the obtained results can outperform the ones obtained by manual tuning each controller parameter individually.

Abstract
In this paper it is described a hardware experimental setup applied to study the response of structures due to an earthquake excitation. The described hardware experimental setup was applied in the performance and effectiveness evaluation of passive and semi-active vibration control strategies, in order to reduce the structural response due to an earthquake excitation. This study is also meant to validate the accurateness of the developed numerical models that simulate the experimental results. The hardware implementation is described, being the structural response real data and its numerical models compared.

Abstract
NaSSIE - Navigation and Sensoring Skills in Engineering is a platform developed with the intent of facilitating the acquisition of some skills by Engineering Students, which is a core part of the process of controlling a mobile robot. In this paper, the chosen hardware and consequent physical construction of the prototype as well as vehicle’s associated software will be presented. As a use case, this platform was tested during the Robotic Day 2017 in Czech Republic. Preliminary results will also be presented of this year’s preparation for the Micromouse competition. © 2019, Springer Nature Switzerland AG.

Abstract
In this paper it is presented a line follower educational mobile robot performance robustness increase. The Robotic Day line Follower Competition was used as a Benchmark to test the proposed approach. The applied robot is based on an Arduino, which is applied in the low level control, while the high level control loop is carried out by an RPI running an object pascal application. The described robot was prototyped in order to have a competitive participation in the Robotic Day Line Follower 2017 competition, and improved for performance robustness increase in order to participate in the 2018 competition. It was prototyped with an RPI, taking advantage of its capabilities, allowing the use of higher performance sensors, when compared with the most common standard approaches based on a single 8 bit RISC micro-controller, having as disadvantage the inevitable robot size increase, which compromises in certain situations the robot maneuverability and increases the power consumption. The robot is equipped with DC Motors, the chosen line follower sensor is the picamera and for the obstacle detection, a time of flight sensor was applied.

Abstract
Since DC Motors are common components in engineering projects that involve process control, it is necessary for any student in this area to understand their concepts, construction and applications. This paper focuses on a series of Laboratory Experiments that were carried out in an Entry Level Unit of the Integrated Master Degree in Electrical and Computers Engineering of the Faculty of Engineering of the University of Porto, named Project FEUP. In this class, mandatory for all students, they learn to how use these motors, from basic concepts to the estimation modeling. The paper presents the developed kits that students use, the simplified model and examples of the experiments performed in some classes.