Abstract
The paper develops and investigates a novel set of constrained-output robust controllers with selectable response smoothing degree designed for an integrator-plus-dead-time (IPDT) plant model. The input-output response of the IPDT system is internally approximated by several time-delayed, possibly higher-order plant models of increasing complexity. Since they all contain a single integrator, the presented approach can be considered as a generalization of active disturbance rejection control (ADRC). Due to the input/output model used, the controller commissioning can be based on a simplified process modeling, similar to the one proposed by Ziegler and Nichols. This allows it to be compared with several alternative controllers commonly used in practice. Its main advantage is simplicity, since it uses only two identified process parameters, even when dealing with more complex systems with distributed parameters. The proposed set of controllers with increasing complexity includes the stabilizing proportional (P), proportional-derivative (PD), or proportional-derivative-acceleration (PDA) controllers. These controllers can be complemented by extended state observers (ESO) for the reconstruction of all required state variables and non-measurable input disturbances, which also cover imperfections of a simplified plant modeling. A holistic performance evaluation on a laboratory heat transfer plant shows interesting results from the point of view of the optimal least sensitive solution with smooth input and output.

Abstract
Two major control design objectives are set-point tracking and disturbance rejection. How to design a control system to achieve the best possible performance for both objectives is a classical research issue. For most systems these design objectives are conflicting meaning that a single controller cannot cope in providing overall good performance. In this paper, a dual mode control system is reported using a feedforward controller to achieve optimum set-point tracking and PID control to deal with disturbance rejection. A particle swarm optimization algorithm is deployed to design the feedforward controller and the magnitude optimum multiple integration method applied to design the PI/PID controllers. The proposed control system is tested on a custom-made laboratory control temperature kit based on Arduino system. Preliminary results are presented showing the dual-mode control potential merits. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

Abstract
Flipped Classroom approach was implemented in an Automation course with around 100 students. Videos focused on GRAFCET topics were given to students prior to class and problem-based challenges were solved in class by the students in a collaborative way. The teacher’s role was to guide students in their learning process. The goal was to identify students’ behavior regarding this learning approach, and the videos in particular, by using questionnaires. Result analysis shows a positive feedback from students motivating teachers to enlarge this learning approach to other courses. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

Abstract
Practice is of the essence in Engineering courses. A relevant question in control engineering education is: How to close the gap between theory and practice? Once subjects are introduced in theoretical classes, students want to know about its practical use. Thus, it is important to introduce theoretical control concepts with practical experiments, enabling students to easily test and validate the theory. An Arduino based temperature control laboratory (TCLab) is deployed in this study as a portable kit providing students with a simple and effective means to test some feedback control techniques. Teaching/learning experiments are proposed involving proportional, integral and derivative controllers with Feedforward and Cascade control structures. Preliminary results achieved in a Portuguese university are presented. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

Abstract
The study analyzed several instruments of the master-integrated course in Electrical and Computer Engineering at a Portuguese Public University. The institutional drivers responsible for adopting new methodologies in the course were evaluated. A case study was carried out with a qualitative approach based on mixed methods: a statistical analysis applied to textual corpus and complemented by content analysis. As a result, two classes of content analysis emerged: skills and knowledge expected from students; and aspects of training in Electrical Engineering and the study cycle. Seven drivers were identified for the adoption of new methodologies in the course, based on the theories of diffusion of innovation and institutional theory: training, development, competence, study cycle, new, technology, and UC. Each of these drivers has its outcomes, 16 in total, which shows the effects perceived by the teachers, course coordinators and evaluators.

Abstract
While living in a digital era, both teachers and students of Engineering Courses were not ready for the drastic change associated with the Covid-19 first confinement (March 2020). This forced change from a presential mode to a fully on-line mode provided teaching/leaning difficulties as well as new opportunities. Moreover, as most engineering courses require laboratory practice, on-line teaching raised additional challenges. This paper reports two different experiences in two different Control Engineering university courses in the North of Portugal. The goal is to share some learning tools that are particularly relevant in the pandemic time we are living: pocket-sized laboratory kits that students can easily take home and experience real-world control contents; an open Mural that can serve as an exchange of knowledge. Perceptions received both from students and lecturers regarding these two experiments are presented.