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Raceway reactors are still the most extensive technology for microalgae production. However, these reactors have some drawbacks, one of them being a low mass transfer capacity, which provokes dissolved oxygen accumulation and thus reduction of system performance. To overcome this problem, it is imperative to improve the photobioreactor design as well as the operating conditions. One solution is to maintain the dissolved oxygen below defined limits. In this work, a new control algorithm is proposed to improve the mass transfer capacity of raceway reactors while at the same time reducing air injection costs. The main idea of the proposed control approach is that only the necessary amount of airflow will be applied according to transfer capacity demand. This control strategy was first analyzed in simulation and compared with classical On/Off solutions, and subsequently evaluated in outdoor conditions in a photobioreactor of 80 m

This paper presents a solution to the saturation problem in cascade control schemes. When cascade control approaches work in linear mode without saturation influence, important improvements can be achieved in industrial control loops. The effect of disturbances and/or nonlinear actuator behaviours on the main process variables can be considerably reduced. However, when saturation arises in the inner loop, these improvements cannot be reached and even sometimes the saturated cascade control scheme gives worse results than a single control loop. Thus, this work analyzes this situation and introduces an alternative solution to solve this problem and to reduce the impact of the saturation effect.

espanolEste trabajo presenta la implementacion de un controlador predictivo generalizado (GPC) para el control del pH en un fotobiorreactor raceway para el cultivo de microalgas. La variable mas critica en los procesos de crecimiento de microalgas es el pH, teniendo relacion directa con la productividad del sistema. La dinamica no lineal del pH se ve afectada de manera directa e indirecta por mas variables del sistema, como el aporte de CO2 al medio de cultivo, el exceso de O2 debido a la realizacion de la fotosintesis por parte de las microalgas, la radiacion solar y la concentracion de biomasa. Este tipo de reactores estan normalmente controlados mediante controladores clasicos todo/nada que no tienen en cuenta el modelo del sistema ni el consumo de CO2. Debido a la importancia de mantener el pH dentro de unos valores determinados que afectan directamente a la productividad, en este trabajo se ha optado por disenar un control predictivo lineal que permita acotar la salida del sistema a los valores optimos que permitan aumentar su productividad, reduciendo el uso de CO2 al mismo tiempo. EnglishThis paper presents the implementation of a Generalized Predictive Control (GPC) algorithm for the pH control in a photobiorreactor raceway for microalgae. The pH is the most important variable in the microalage crop growth process, which has a direct inuence on the system productivity. The nonlinear dynamics of the pH is affected by other system variables such as CO2 supply, excess of O2 due to the photosynthesis process, the solar diation and the biomass concentration. This type of reactores are usually controlled by means of on/off controllers, which do not take into account the process model and the CO2 consumption. To keep the pH within an specific range is very important and affects directly the system productive. Thus, a constrained predictive control is designed in this work to limit the pH with the optimal values allowing to increase the productivity and to reduce the CO2 consumption.

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 PID controller is designed by using Quantitative Feedback Theory to account for these uncertainties and to fulfill robust specificaitons for the regulation control problem. Results based on frequency and time domains are presented.

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 Almeria, 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.

In this paper, a control scheme based on feedback linearization technique and quantitative feedback theory (QFT) is used to regulate the inner diurnal temperature in a greenhouse located in the south of Spain. In a first step, a non-linear model for the greenhouse is used to design a feedback linearization controller, which provides the vents opening percentage from a virtual control signal provided by a robust proportional integral (PI) controller. The relation between the system output (inside temperature of the greenhouse) and the virtual control signal is given by a first order plus dead time (FOPDT) system. The values for the three parameters of this linear model are identified in the experimental greenhouse by applying several step changes in the virtual control signal and analyzing the process response. Different values for gain, the time constant, and time delay are identified. So, this uncertain linear description for the system is used to design a quantitative feedback theory (QFT) controller with a PI structure. Finally, experimental results are analyzed showing satisfactory performance of the proposed control approach.

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.

Jornadas de Automática (37ª. 2017. Gijón), Este trabajo ha sido nanciado con el Proyecto del Plan Nacional DPI2014-55932-C2-1-R del Ministerio de Economía y Competitividad y Fondos FEDER.