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We describe the process of creating a control themed advent calendar quiz by means of a joint effort of researchers involved in control education from different countries, of distributing it among our students, and of collecting and analysing feedback from who answered the quiz. The created calendar consists of 24 problems, one for each of the 24 days before Christmas, and has been proposed to university students with the aim of showing them the many aspects that control engineering touches upon, and how this discipline can be useful in a wide variety of applications. We thus discuss the lessons learned from carrying on this initiative, with the purpose of aiding the creation and management of similar ones by listing what we believe are good practices in collaboratively creating quizzes, and in general what we believe may improve control education and serve as a valuable measure for outreach.

In 2023, a group of control academics joined to create a control themed advent calendar, which was open for participants from several European universities. A survey was used to collect participants’ feedback at the end of the activity. The results show that the calendar was mostly perceived as a fun and enjoyable activity, increased the perceived relevance of control as well as the perceived ability to solve control questions and that the questions were in general neither too difficult nor too easy. Some room for improvement was also identified.

Gamification refers to the utilization of gaming methods and tactics in non-traditional areas, like education. In this work, we describe different gamification-based methods for teaching automatic control in engineering studies as an alternative or support to the traditional teaching system. The experiences are being developed within the framework of a teaching innovation project developed at the University of Almería (Spain). The main objective of this project is to analyze the academic feasibility and acceptance of the use of gamified experiences by both professors and students. Specifically, the paper gives an overview of three different types of games. The first is a solitaire-style card game focused on the reinforcement of the theoretical concepts related to open-loop dynamic system analysis and the design of closed-loop control systems. The second is a virtual challenge of tuning Proportional, Integral, and Derivative (PID) controllers. The goal of this game is for students to understand the impacts of proportional, integral, and derivative actions when these controllers operate in closed-loop mode. The third is an escape room with the primary objective of improving students’ comprehension of basic control principles covered in the initial introductory course in engineering studies.

Plants with integrators possess control-relevant modeling requirements that are typically ignored in the literature. Desired closed-loop speeds of response for such systems can differ significantly from their open-loop dynamics, causing conventional system identification guidelines to fail or be inaccurate. One such issue relates to experimental design. This paper presents guidelines for the design of excitation signals for system identification of plants with integrators, with application to the modeling and control of a microalgae raceway reactor. The concept is to excite the system through optimized test signals with control-relevant shaping of their power spectra. This facilitates a shift in emphasis of the identification objective from estimating a model with good open-loop performance to having a model possessing desired closed-loop characteristics. Such a consideration is particularly important when generating informative databases for estimating predictive models for closed-loop control. An illustration for this experimental design procedure is accomplished in this paper through the estimation of ARX-based models and, subsequently, model predictive control of the pH dynamics of an experimental raceway photobioreactor facility hosting sustainable microalgae production.

This work introduces a Fractional Order PID (FOPID) controller associated with a nonlinear Filtered Smith Predictor (FSP) to control a Solar Collector Field (SCF) system. The combined approach enhances the control performance by decoupling model uncertainties. First, the FOPID addresses linear model uncertainties through optimal robust design across the operational conditions, while the FSP compensator adeptly manages the system’s varying time delays. Rigorous tuning in the frequency domain considering closed-loop, robustness, and disturbance rejection performances is developed using a bi-level optimization approach to obtain the FOPID control parameters. Experimental results of the FOPID + nonlinear FSP demonstrate low rise time for reference tracking and robust stability across several operating conditions, even in the face of high-frequency disturbances in the solar irradiance due to passing clouds. Moreover, the nonlinear FSP effectively handles variations in time delays undergone by the water flow variation during the experiment. The achieved outcomes of the overall control structure, comprising the FOPID + FSP, demonstrate a promising approach for SCF system control, obtaining robust behavior in the presence of model uncertainties and disturbances while offering satisfactory reference tracking capabilities across an extensive range of plant operations.

This study performs a comparative analysis of three Model Reference Adaptive Control (MRAC) schemes grounded in Lyapunov theory. Specifically, it compares a pure MRAC controller with two hybrid MRAC-PID schemes, each integrating the PID component in a distinct manner within the control structure. The aim is to address a significant gap in the existing literature related to the lack of comparisons involving the different ways the MRAC and PID control can be hybridized. The developed controllers undergo extensive testing in simulated scenarios emphasizing model reference convergence and disturbance rejection. The results underscore that hybridizing the MRAC mechanism with a PID controller offers notable advantages in both performance and robustness, especially concerning disturbance rejection, a scenario in which the hybrid controllers improved by around 70 and 75% the mean square error obtained with a pure MRAC controller. In general, these findings highlight the potential benefits of combining MRAC and PID techniques, providing insight into the improved control system performance that PID control can bring to conventional MRAC schemes.

The aim of this paper is to emphasize the importance of PID control for our society in general and for the control engineering community in particular. To this end, we first equate the relevance of PID controllers with other inventions in history to remark how PID control has contributed to revolutionizing our world as the main ambassador of the automatic control field. Afterwards, the PID control resilience is provided by showing a brief historical evolution to realize its timely adaptation, and how nowadays it is much more than just the three terms; P, I, and D. Moreover, it is summarized how PID control has been demonstrated to be equivalent to other optimal control solutions and how the recurrent comparison with Model Predictive Control (MPC) is not necessary at all, as both control algorithms should be considered as complementary approaches. Finally, encouragements and suggestions are summarized to continue working on PID control topics.

This work presents an approach for PID control and optimization in a distributed system, using the IEC 61499 control standard. This standard enables communication among different PLCs, which are used to develop a three-layered event-driven control of a SISO loop. The lowest layer is in charge of cyclical data acquisition. The second layer carries out an event-based PID control. The highest layer runs a control optimization algorithm, specifically a simple tuning approach based on Ziegler-Nichols that is used to determine the PID parameters for different operating points. The proposed approach is assessed in a tank level SISO control problem, whose behavior can be modeled as a first-order plus dead time system in each operating point. For that purpose, it has been implemented using two PLCs and a software PLC running on an industrial computer. The experimental results on the SISO level control loop show the feasibility of the proposed approach for event-driven control in a distributed system and open interesting research questions in the intersection of controller design and distributed automation.

This paper describes i-pIDtune 2.0, an updated interactive software tool that integrates system identification and PID controller design. The tool supports experimental design and execution under plant-friendly conditions, high-order ARX estimation, and control-relevant model reduction leading to models that comply with IMC-PID tuning rules; these controllers can then be evaluated in simulation. All four stages are depicted simultaneously and interactively in one screen. The updated tool includes two significant new features: 1) support for “bumpless” PI-D and I-PD closed-loop simulations that provide a broader understanding of PID tuning effectiveness in practical settings and 2) extension to plants with integrating dynamics. These new features are described and illustrated with two example problems.

This paper presents the simulation implementation of classical control strategies based on PID controllers for the simultaneous control of water level and biomass concentration in open reactors by manipulating the dilution (inflow) and harvested (outflow) flow rates. The system studied is a TITO (two inputs-two outputs) process with coupling between its variables, and a significant amount of disturbances, such as solar radiation, relative humidity and ambient temperature. The proposed strategies combine Controlled Variable (CV) and Manipulated Variable (MV) switching strategies to follow both setpoints and overcome saturation problems. A simulation of six consecutive days with different external climate conditions was performed. The results show that the proposed schemes can significantly improve the basic PID control performance. The proposed solutions are simple and generic, and behaving properly for both controlled variables.

This work presents a novel demonstration-scale integration of a 36-m2Fresnel solar collector in urban wastewater reclamation. A prototype plant was designed and installed to study Escherichia coliand total coliforms disinfection in continuous flow mode. The plant modelling was empirically addressed, resulting in different linear first-order models, which were used to design a PI-based cascade control approach for the automatic operation of the photoreactor. Considering EU 2020/741 Regulation, water quality Class D and Class A were achieved when operating the upgraded design of the plant at 50°C (200 L/h) and 60°C (150 L/h), respectively.

Greenhouses provide controlled environments for cultivating crops. This work explores the design of PID-based greenhouse climate control techniques using natural ventilation, considering both measurable disturbances and operational constraints. A nonlinear model was developed to relate natural ventilation (the primary climate actuator) with interior temperature in greenhouses, the critical factor being the relationship between air flow rate and vent aperture, which is a source of uncertainty in the related literature. Novel calibration issues are included for this term. The nonlinear model is used to devise control strategies combining PI control and feedback linearization. The resulting simulations and robustness analysis, which accounts for uncertainties in the relevant parameters, demonstrate that the combination of PID and feedback linearization techniques is a suitable control approach. In summary, practical tradeoffs can be achieved between setpoint tracking, disturbance rejection, control effort, and robustness.

Microalgae production in raceway photobioreactors is a very attractive process for biomass production because of its high sustainability. This paper presents a complete methodology for optimizing production in raceway photobioreactors. A first principles model has been developed that describes the dynamics and steady state of the system and has been used as the core of a real-time optimization to maximize the economic profit of the process, which handles the references of different variables of the system. For that, a steady-state real-time optimization approach complemented with PID controllers is presented in this work. The results obtained demonstrate the potential of steady-state real-time optimization for such systems, as well as the benefits of employing optimization techniques during process operation.

As a response to the scarcity of workforce with essential competences for Industry 4.0, academic institutions are making an effort to propose specialized educational programs. In this context of digitalization, industrial cybersecurity is an increasingly important aspect. Nevertheless, industrial cybersecurity is a challenging topic that requires the understanding of both information technologies and the operation of industrial facilities. Furthermore, practical training requires realistic environments to be useful. For this reason, in this work, we present a hands-on activity on a remotely accessible training platform to complement the theoretical concepts of a Master's degree course that deals with the introduction to industrial cybersecurity. This platform presents the students a realistic automation environment with industrial hardware and software. The educational experience has been assessed with regard to the students’ perception and its technical operation. The platform was found useful for learning and motivating, although the perceived degree of difficulty needs to be adjust to promote students’ self-confidence.

Inrecent years there has been a revolution in the development of interactive applications for teaching control theory. In parallel, much work has been done on the development of experimental and virtual control laboratories. In this work, different interactive tools are presented that aim to link both worlds with the aim of promoting the link between theory and practice, using the most common equipment that can be found in automatic control laboratories.

This paper treats the problem of feedforward control from measurable load disturbances. Most of the tuning rules based on IAE or ISE optimization for feedforward compensators that have been presented in recent years are compared with each other as well as with optimal compensators. There are two different feedforward control schemes that may be used, and these schemes are also compared and analyzed. The paper gives recommendations for selection of both control schemes and tuning rules.

In the context of material synthesis and thermal stress tests, solar furnaces play a fundamental role. These experimental systems are usually operated manually by trained operators. However, the use of automatic controllers can be essential to take into account the different dynamics of the treated materials, follow the different temperature profiles required in the tests, meet system security requirements, and face the intermittency of the main energy source, the solar energy. On these bases, the present work proposes a control system for temperature regulation in solar furnaces. The controller is based on a nonlinear model predictive control strategy that deals, in a single control layer, with the nonlinear behaviour of the system, the effect of disturbances, and the system's operating constraints. The controller was experimentally tested in the solar furnace SF60 of Plataforma Solar de Almería (southeast Spain), showing adequate performance against setpoint temperature changes, reaching a settling time of the order of 54 % faster than the open-loop system's time constant, and effectively rejecting irradiance disturbances. In addition, the operational constraints were ensured in almost all operating circumstances, observing only slight deviations of less than 2°C. These results allow us to position the proposed controller as a relevant tool for daily operation.

This work presents a multivariable control strategy to regulate nighttime temperature and relative humidity inside a greenhouse, using a pipe heating system and a dehumidification system. The greenhouse is modeled as a two-input two-output (TITO) process with a system identification methodology to calculate low-order linear models. Proportional-integral (PI) controllers with anti-windup are used, and an inverted decoupling scheme is adopted. The strategy was tested in simulation with real data. Results suggest that it is attractive for real implementation and show for the first time that the use of dehumidification systems can be applied as part of a combined control strategy.

The industrial production of microalgae is a highly sustainable and attractive process due to its variety of applications, especially when it is combined with wastewater treatment. From a control point of view, the optimization of the process requires a considerable effort regarding the culture conditions. The biological nature of the process renders its characterization considerably difficult, as well as the acquisition of models describing its dynamics. In this work, a complete methodology for pH control in raceway photobioreactors based on the Practical Nonlinear Model Predictive Control (PNMPC) approach is proposed. Models based on artificial Neural Networks (ANN) of the system have been obtained and validated, and a PNMPC controller based on these data-driven models has been developed and tested in a real raceway reactor. The results demonstrate the reliability of this type of models, and justify the possibility of combining them with predictive control algorithms in highly nonlinear systems.

This article describes the experience of using commercial, affordable, and portable Arduino-based kits to teach automatic control in different engineering courses at the University of Almería, Spain. The kits, named APMonitor Temperature Control Lab (TCLab), were provided to undergraduate and master's students and used as real systems to perform open-loop and closed-loop tests that help to complete a series of practical exercises. A description of how TCLab was used in five different courses together with examples of the proposed exercises are given, which could serve as inspiration to lecturers and educators for designing their own proposals. In particular, results are presented for model calibration by means of the least-squares algorithm, and for predictive control algorithms. According to the students’ feedback, obtained via an anonymous survey and open debates, it was challenging (but very motivating) to work with TCLab. Most of them also consider it a flexible and suitable platform for grasping control engineering concepts.

This article describes the experience of the Automatic Control, Robotics and Mecha-tronics Research Group from the University of Almería in the participation and preparation of workshops for teaching programming, control engineering and robotics to young students. All the activities designed to encourage the study of STEM careers among young students are described. Some activities are focused on directly promoting Automatics and Robotics disciplines. Others deal with encouraging the participation of women in science, and so, breaking gender inequality. Two main workshops, where first- and second-year students collaborate directly with the University of Almería, are also described in detail. Finally, this paper shows the growth in the number of students who enrolled in engineering degrees thanks to these dissemination activities.

This paper aims to analyze some different solutions that were adopted in control education activities during the pandemic. The authors of this paper are educators in the control education field from different countries on all the continents, who have developed a questionnaire with the idea of collecting data about the COVID-19 pandemic impact on the control education activities. The main objective is to study the diverse alternatives that were used worldwide to perform the online educational activities during that period, such as methodologies, tools, learning management systems (LMS), theoretical exercises, laboratory experiments, types of exams, simulators, software for online lecturing, etc. As a result, comparisons between pre-and during-pandemic educational resources and methods are performed, where useful ideas and discussions are given for the control education community.

Research and teaching on renewable energies are very important topics worldwide. Most of the renewable energy processes are quite complex to analyze and to study. For that reason, educational resources as support for the teaching and learning of these processes dynamics are very useful. Thus, this paper presents a virtual lab as support to the modeling and control concepts of a solar collector field, as these kind of solar plants are widely used at industrial level requiring control skills. This interactive tool is used as part of several subjects in a Master on Solar Energy at the University of Almería, Spain. Examples about open and closed-loop exercises are presented.

This work presents a new architecture to use greenhouse models as a service in an Internet of Thing (IoT) paradigm. Traditionally, models are implemented in specific programming environments for research purposes or coded within a software tool that can be used as Decision Support System (DSS) by companies or farmers. In the solution presented in this paper, the models are available in the cloud and they can be accessed as a service through Internet from any software tool or any device (computer, tablet or smartphone). On the other hand, the models can be accessed as DSS or as a simulator for control purposes. Examples for researcher and end-user points of view are presented for a tomato crop growth model.

This paper presents an active disturbance rejection control scheme to automatically regulate the glucose level in type 1 diabetic patients. Although the blood glucose system is nonlinear, in this control approach, it is represented as a linear perturbed system, whose lumped disturbance input is estimated by an Extended State Observer (ESO) and then compensated by an robust controller tuned with Quantitative Feedback Theory (QFT). The robust control scheme uses a Smith predictor for the time delay compensation and allows taking into account the inter-patient variability presented in the glucose control problem.

This paper describes a model-based control approach for the pH regulation in raceway photobioreactors. The pH variable is the most important one in the photosynthesis rate and it must be controlled within an specific range. The microalgae system is a very complex process that makes difficult to obtain simple models for control purposes. Usually, first-order models are used to describe the pH dynamics in the system and to design control algorithms. However, sometimes more complex models are required to capture the dynamics of the system and to cope with a wider operating range. For that reason, in this work, a Wiener model is presented for the pH variable looking for a trade-off between model accuracy and complexity, and where linear and nonlinear dynamics are combined. Afterwards, this model is used in a model-based control approach that allows to decouple the linear and nonlinear terms. The control scheme is based on a PID controller and a robust filter. Simulation results will show the promising behaviour of the proposed control solution.

This paper treats development and research at the regulatory control layer in process control. It is noticed that very little attention is payed to this subject, with the exception PID controller tuning. The reason for this is discussed. Two examples of recent advances in the field treating feedforward control and ratio control, respectively, are presented. A goal of the paper is to point out the need for further research in the area. One reason for this is the great industrial impact such research may have, since the functions appearing in this layer are used at so many places in so many industries. A second reason is the need for well functioning regulatory control layers to form solid foundations for the advanced process control layers.

This paper presents the methodology followed to evaluate students ability to face the challenge of controlling a refrigeration system based on vapour compression proposed as a benchmark for PID control design in the PID18 Conference. This benchmark has been also proposed as test-bed plant for the design of controllers in the subject Industrial Control Techniques at the University of Almería, Spain. The solutions proposed by the students range from simple SISO PID control loops (including anti-windup effect) to MIMO ones, including decoupling, filters and feedforward action to reject disturbances. All these solutions rely on models obtained from the reaction curve method. The selection of adequate specifications is encouraged, although students creativity has led them to exploit very aggressive specifications taking into account the different system restrictions, and obtaining very good values of the proposed evaluation indexes. © Copyright IFAC 2018.

This document addresses the problem of controlling a one-stage refrigeration cycle by using the opening of the expansion valve and the compressor speed as control variables, while the outlet temperature of evaporator secondary flux and the superheating degree of refrigerant at evaporator outlet are the controlled variables. An uncertain matrix function is obtained in order to represent the full operating range of the nonlinear system. Thus, the control decentralized approach control consists of designing Generalized- Proportional-Integral (GPI) observers for the internal loops of each controlled variable while PID controllers are tuned based on the Quantitative Feedback Theory for the respective external loops. Simulations results show that the robust controllers reacts quickly reference settings, despite the non-measurement of the disturbance variables and the dynamic coupling of the multi-variable system, compared to decentralised single PIDs proposed with the benchmark.

This paper presents the modification of the well-known pole placement method for first-order systems and PI control for the tracking problem. The main drawback of the original method is the presence of a zero in the closed-loop transfer function, which has a negative influence in the desired closed-loop response. Typically, this effect is cancelled by using a reference filter within a two-degree-of-freedom control scheme. However, in this work we present a simple modification of the original method that allows us to consider the zero effect in advance. First, the effect of a zero term in the response of second-order systems is analyzed to see how the time response parameters (overshoot, peak time, rise time and settling time) are affected. Afterwards, this analysis and the resulting equations are combined with the pole placement method to propose the new solution. Finally, simulation results are presented to demonstrate the advantages of the proposed method, where it is shown that faster responses than by using a reference filter are obtained.

This paper presents a multivariable TITO (two inputs two ouputs) controller aimed to improve the start-up procedure of a Solar Membrane Distillation (SMD) facility, located at Plataforma Solar de Almería (PSA). The control structure includes PID controllers and decouplers, as well as a reference governor based on a real time optimizer. The filtered Smith Predictor (SP) control structure has been used for controlling one of the output variables, whereas a cascade control scheme is employed to control the other one. The proposed approach has been tested in simulation on a nonlinear model of the SMD facility, showing promising results.

Feedforward control schemes to compensate for disturbances are very well known in process control. In those control approaches, PID controllers are usually considered in the feedback loop, where nominal design for both feedback and feedforward controllers are commonly performed. This paper presents a robustness analysis to study how uncertainties can affect the classical feedforward control scheme. Afterwards, a robust PI controller is designed by using Quantitative Feedback Theory to account for these uncertainties and to fulfill robust specifications for the regulation control problem. Results based on frequency and time domains are presented.

This paper presents ongoing project to develop new interactive books for control education. The novelty of the proposed idea is to merge web-based solutions with LaTex text into a epub format. In such a way, classical interactive tools for control education are combined with static text and thus interactive books are created, being compatible with standard e-book readers. A book chapter about the teaching of second-order processes is presented as example to show the different steps and the results of the proposed idea

In this work, a Proportional-Integral-Derivative (PID) controller based two-degree-of-freedom control scheme for Depth of Hypnosis (DoH) in general anesthesia is proposed. This approach uses the Bispectral Index Scale (BIS) as a controlled variable and propofol administration as a control variable. The developed structure applies a new compensation scheme, which reduces the influence of the nonlinear element. In this context, we exploit the linear part of the patient model, that can be obtained from the demographics of each individual patient. The parameters are tuned using the optimization procedure based on a genetic algorithm. The evaluation of the proposed technique is performed using intra-patient variability with a Monte Carlo method. Additionally, the performance of the analyzed system has been verified using several indexes. The simulation results show that desired characteristics are obtained for both induction and maintenance phases.

This paper presents new simple tuning rules for the gain in feedforward compensators. When the ideal feedforward controller is not possible to implement, a negative effect is introduced in the closed-loop response. So, the closed-loop transfer function from the disturbance to the error is analyzed and tuning rules for the feedforward gain are proposed. Two feedforward structures are used, a lead-lag compensator and a static controller. First, the feedforward gain is tuned to reduce the overshoot in the response for both compensator structures. Afterwards, a second tuning rule for the feedforward gain is derived to minimize the integrated absolute error. Finally, the different tuning rules are evaluated through simulations and compared with other existing solutions in the literature.

This paper presents the design and the prototype implementation of a low cost embedded controller for a greenhouse selective spraying vehicle. The objective was to develop a tailored and modular control system composed by: main controller module, ultrasonic detection module and valve driving module. The ultrasonic sonar module is used for detecting the crop lines. It allows avoiding application of plant protection products in zones without crop coverage. On the other hand, the developed embedded unit incorporates a nonlinear pressure controller, which is used to regulate the working pressure of spraying systems. Laboratory tests demonstrated that the application of ultrasonic sensors with embedded pressure controller gives a possibility to achieve an important improvement in pesticide application tasks. The main benefits can be obtained in reduction of greenhouse soil contamination, which is achieved by an intelligent spraying algorithm using a low-cost solution based on the developed system.

This paper deals with a predictive disturbance compensator for processes characterized by input-output and disturbance-output time delays. The proposed scheme provides a solution for configurations where the application of classical feedforward approach results in poor performance. The analyzed technique merges the advantages of classical feedforward control scheme, which can be combined with any feedback controller, and the use of future disturbance estimation in the predictive control mechanism. The predictive compensator is based on the GPC (Generalized Predictive Control) algorithm exploiting its prediction capabilities. The evaluation of the proposed disturbance rejection scheme is performed through simulation and compared to common techniques in order to highlight the advantages and drawbacks. The obtained results show that the proposed approach can significantly improve the disturbance attenuation in process control tasks.

This paper presents a library of MATLAB classes developed to provide a framework to allow performing easy and scalable process control simulations. The proposed object-oriented tool features the basic components of a control loop including: processes, controllers, sensors, actuators and connection links. The simulator can be configured to carry out simulations with continuous and/or discrete elements, and/or include event-triggered capabilities in a straightforward manner. The benefits of the proposed library are shown with the rapid development and simulation of a quadruple-tank system that is controlled by means of a PI controller.

This paper presents simple tuning rules for low-order feedback and feedforward controllers based on an approximation of the filtered Smith predictor with closed-loop feedforward compensation. An analytical development is introduced to control stable first-order plus dead time processes affected by measurable disturbances that cannot be completely removed from the process output due to dead-time effects. Simulation results for the pH control of a tubular photobioreactor and the steam pressure control of an industrial boiler are given to show the effectiveness of the proposed method.

This work presents a simulation study of an event-based selective control strategy for a raceway reactor. The control system aims are to maintain simultaneously a pH and dissolved oxygen within specific limits. In the analyzed control scheme, the pH value is prioritized over the dissolved oxygen, since it has a critical influence on the process performance. Besides, the dissolved oxygen also influences the photosynthesis rate and should be kept within the limits. The control structure is evaluated through simulation, where a nonlinear model for microalgae culture in the raceway photobioreactor is used. Analysis of different configurations allows to determine the most adequate control system setup to achieve the desired goals. The obtained results show that combination of an event-based approach with selective control allows to increase the overall productivity as well as to address effective CO2utilization and aeration system energy minimization.

The main objectives of SCADA (Supervisory Control And Data Acquisition) systems are the supervisory analysis of the system, control algorithms validation, and data acquisition. These systems are normally implemented according to the international standards: UNE-EN ISO 9241, ISAIOI-Human-Machine Interfaces, ISA S5, and in the case treated in this paper The Spanish Royal Decree 488/1997. This paper presents a software architecture for the development of educational laboratories, through industrial virtual plants which models and logic are implemented in Matlab® and used within LabVIEW® through an appropriate protocol. Lab VIEW® from National Instruments, a specific purpose software for this kind of applications, was used, since it allows us to provide a friendly interface, to perform communications, data acquisition and the information management. In addition, to illustrate the use of the proposed architecture, different virtual industrial plants for students of different Bachelor and Master degrees in engineering at the University of Almeria have been developed. This paper shows the different virtual industrial plants that have been developed using SCADA systems to facilitate students’ learning of basic concepts and techniques for an Industrial Informatics course.

This work presents the development of a hierarchical control strategy for microalgal production. The proposed control scheme is composed of two layers. A lower layer focused on pH set-point tracking and where two different control algorithms were evaluated, a PI plus feedforward compensator and a Practical Non-linear Model Predictive Controller. The upper layer is in charge of calculating optimal pH set-points based on economic criteria to maximize profits, computed as the difference between the incomes obtained from the final production sale and the associated production costs (including the environmental impact of the exhausted CO2losses). Two types of models have been used depending on the requirements of each layer. Simulated results of the proposed hierarchical control architecture are presented.

This paper presents the idea about how to combine a set of software and hardware resources available in literature to be used as support to control engineering education. The available tools allow to mix topics related to programming, communications, operating systems, and control theory. The well-known Raspberry Pi board is used as platform to exploit the di_erent proposed concepts. SciPy, Matplotlib, and NumPy libraries, which are Python-based open-source libraries for scienti_c computing and graphical representation, are used to perform Matlab-like simulations and to implement classical control loops. On the other hand, virtual processes developed in Easy Java Simulations are adapted to be controlled through the network from a controller implemented on the Raspberry Pi with Python. This option is very useful from a teaching point of view since time-based, networked-based, or event-based control approaches can be easily introduced on this proposed architecture. Furthermore, once students know how to implement control loops on the Raspberry Pi using Python, external real processes can be easily controlled by using the GPIO interface available in the this electronic board. Then, a project based on these tools and ideas is motivated and presented in this paper to control a two-tank level process © Copyright IFAC 2015.

Prior work by the authors (featured in software sessions held during SYSID 2009 and 2012) described ITSIE and ITCRI, a series of interactive tools designed to aid students and practitioners in better understanding the role of design variables associated with classical prediction-error and control-relevant identification, respectively. This paper presents ITCLI (Interactive Tool for Closed-Loop Identification), an interactive software tool for understanding design variables in closed-loop identification of LTI SISO systems using prediction-error techniques. The tool enables an interactive evaluation regarding how bias and variance effects are manifested when identification is performed under closed-loop circumstances. The role of external signal design, choice of model structure, controller tuning during identification testing, and signal injection points (at either the manipulated variable or the setpoint) while in the presence of autocorrelated disturbances can be evaluated in a comprehensive and easy-to-operate tool. The software is developed using Sysquake and is provided as a stand-alone executable version in the Windows and Mac OS operating environments.

This paper describes a predictive event-based control algorithm focused on practical issues. The Generalized Predictive Control scheme is used as predictive controller, and sensor and actuator deadbands are included in the design procedure to provide event-based capabilities. The first configuration adapts a control structure to deal with asynchronous measurements; the second approach is used for asynchronous process updates. The presented ideas, for an event-based control scheme, conserve all of the well-known advantages of the adaptive sampling techniques applied to process sampling and updating. The objective of this combination is to reduce the control effort while the control system precision is maintained at an acceptable level. The presented algorithm allows to obtain a direct tradeoff between performance and number of actuator events. The diurnal greenhouse temperature control problem is used as test bench to evaluate the different control algorithms configurations.

In this paper, the pH boundary control problem of a tubular photobioreactor is treated. The method of characteristics is used to transform the hyperbolic system of equations into a set of first order ordinary differential equations without approximation. The proposed approach is geometric in nature. The method is shown to be effective in controlling pH concentration of a tubular photobioreactor through simulations under real data disturbances.

This paper deals with a symmetric send-on-delta PI control strategy for controlling the internal temperature of a greenhouse. It is shown that, by properly designing the control system, the disturbances represented by the soil temperature, the solar radiation, the wind velocity, and the outside temperature can be effectively compensated with a limited number of events. The role of the design parameters is outlined and simulation results demonstrate the efficacy of the methodology by comparing it with previously proposed techniques.

This paper describes ITCLI, an interactive software tool for understanding SISO closed-loop identification using prediction-error techniques. The tool enables an interactive evaluation regarding how bias and variance effects play a role in identification under closed-loop circumstances. The role of external signal design, choice of model structure, controller tuning during identification testing, and signal injection points (at either the manipulated variable or the setpoint) all under the presence of autocorrelated disturbances are considered. The software is developed using Sysquake and is provided as a stand-alone executable version in multiple operating environments.

Hundreds of PID design methods are available in literature. Many of them are very similar and sometimes it is not straightforward to understand their purposes. This paper presents an interactive software tool to help in the study and understanding of several well-known PID tuning rules. Frequency- and time-domain responses are analyzed in order to show the robustness and performance properties of each method. Furthermore, a free tuning option is available to provide comparisons with user-defined rules or other existing tuning methods. A wide range of stable process models are included in the tool, where model-reduction techniques are applied for high-order processes to obtain simple models for design purposes.

This work is devoted to analyze the Generalized Predictive Control (GPC) strategy considering measurable disturbances. This well known control architecture is extended using Double Exponential Smoothing (DES) technique to perform future disturbance estimation. The disturbance models are obtained, validated, and embedded within a GPC controller to compensate for future disturbances. The proposed system is compared with a typical GPC without feedforward action, a GPC with feedforward considering constant disturbances in the future, and a GPC with feedforward taking the original real data in the future. The proposed control scheme was tested by simulation of a greenhouse inside temperature control. The obtained results show that the GPC with disturbance forecasting provide improved behavior that standard techniques.