M. Berenguel

Heuristic knowledge-based heliostat field control for the optimization of the temperature distribution in a volumetric receiver

Abstract The paper presents the development and implementation of a heuristic knowledge-based heliostat control strategy optimizing the temperature distribution within a volumetric receiver at the Plataforma Solar de Almeria (PSA) power tower plant. The experience in operating the plant has been used in the development of an automatic control strategy that provides an appropriate flux distribution within the volumetric receiver in order to obtain a desired temperature profile, and allows for operation without a continuous intervention of the operator, which is one of the main characteristics and drawbacks in the exploitation of these kinds of plants. Experimental results are included and discussed in the paper.

Dynamic model of microalgal production in tubular photobioreactors.

A dynamic model for microalgal culture is presented. The model takes into account the fluid-dynamic and mass transfer, in addition to biological phenomena, it being based on fundamental principles. The model has been calibrated and validated using data from a pilot-scale tubular photobioreactor but it can be extended to other designs. It can be used to determine, from experimental measurements, the values of characteristic parameters. The model also allows a simulation of the systems dynamic behaviour in response to solar radiation, making it a useful tool for design and operation optimization of photobioreactors. Moreover, the model permits the identification of local pH gradients, dissolved oxygen and dissolved carbon dioxide; that can damage microalgae growth. In addition, the developed model can map the different characteristic time scales of phenomena inside microalgae cultures within tubular photobioreactors, meaning it is a valuable tool in the development of advanced control strategies for microalgae cultures.

Temperature control of a solar furnace

An application of an automatic control strategy to a solar plant for material treatment has been shown. Since these kinds of plants are manually operated by skilled operators, the development of an automatic control strategy aimed at achieving adequate results throughout the wide range of operating conditions, under which these plants operate, represents an important improvement towards facilitating operation and obtaining desired performance. The control scheme presented is based on a PI controller which incorporates feedforward compensation, an anti-windup mechanism and actuator slew rate constraint handling, both in fixed and self-tuning configurations. It has been developed and applied to the control of a solar furnace for samples of different materials under extreme temperature profiles. Different plant results have been shown and both advantages and drawbacks of the scheme have been commented on.

Effective utilization of flue gases in raceway reactor with event-based pH control for microalgae culture

This work addresses effective utilization of flue gases through the proper pH control in raceway reactors. The pH control problem has been addressed with an event-based control approach using a Generalized Predictive Controller (GPC) with actuator deadband. Applying this control strategy it is possible to reduce the control effort, and at the same time saving control resources. In the pH process case, the event-based controller with actuator deadband can be tuned to supply only necessary amount of CO2 to keep the pH close to its optimal value. On the other hand, the evaluated control algorithm significantly improves the pH control accuracy, what has a direct influence on biomass production. In order to test the performance of the event-based GPC controller, several experiments have been performed on a real raceway reactor. Additionally, several control performance indexes have been used to compare the analyzed technique with commonly used on/off controller.

Application of Predictive Sliding Mode Controllers to a Solar Plant

This brief presents the application of different predictive sliding mode controllers to the control of the outlet oil temperature of a field of distributed solar collectors. These controllers have been tuned based on a first-order plus dead time model that can be easily obtained with the reaction curve method. Satisfactory results have been obtained and several experimental tests showing the tracking and disturbance rejection capabilities are shown and discussed.

Event-based control and wireless sensor network for greenhouse diurnal temperature control: A simulated case study

Traditionally, greenhouse installations have required a great effort to connect and distribute all the sensors and data acquisition systems. These installations need many data and power wires to be distributed along the green-houses making the system complex and expensive. For this reason, and others such as unavailability of distributed actuators, only individual sensors are usually located in a fixed point of the greenhouse selected as representative of greenhouse dynamics. On the other hand, the actuation system in greenhouses are usually composed by mechanical devices controlled using relays, being desirable to reduce the number of commutations of the control signal from security and economical point of views. The greenhouse climate control can be represented as an event-based system, where low-frequency dynamics variables have to be controlled and this control usually acts against events governed by external disturbances. Therefore, this work presents preliminary ideas and results of wireless sensor network and event-based control applied to the greenhouse climate control problem.

Hybrid Modeling of a Solar Cooling System

Abstract Solar systems are deeply affected by weather conditions and their main energy source, irradiation, cannot be manipulated. This paper describes a solar cooling system located at the University of Almeria, Spain. The system is composed by a solar collector, a gas heather, and two serial connected tanks to storage hot water. They are used as energy sources for an absorption machine whose objective is to obtain chilled water for the fan-coil system. All these components are included or excluded from the cooling system by means of switching valves and activating or deactivating signals. The switching among different configuration modes in real time increases the system challenge to be modeled or controlled, due to the mix of both discrete signals and continuous dynamics. In this paper, a model for each energy source is developed and afterwards they are integrated into one state-space model used to obtain a hybrid model. This hybrid model is able to simulate the different configuration modes of the solar cooling system. Some real tests are presented.

Localization and control of tracked mobile robots under slip conditions

This paper deals with the localization and trajectory tracking control problems of tracked mobile robots under slip conditions. The proposed control law consists of the modification of a well-known control algorithm based on the feedback linearization technique, in which additional parameters have been included in order to compensate for the slip effects. Furthermore, an Indirect Kalman Filter has been used to improve the localization of the robot. Real tests show promising results.

The influence of event-based sampling techniques on data transmission and control performance

Event-based systems are becoming increasingly commonplace, particularly for distributed real-time sensing and control. Furthermore, remote monitoring and control through data-communication networks are very popular for process supervision and control. The usage of networks provide many well-known benefits, but it also presents some limitations in the amount of transmitted data. This fact is especially visible in Wireless Sensor Network (WSN), where the bandwidth of communication channel is limited and typically all nodes are battery powered. Event-based sampling techniques appear as a some possible solution to face this problem allowing considerably saving network resources and reducing the power consumption. On the other hand, the control system performance is highly affected due to the event-based sampling techniques, being necessary to analyze and study a compromise between control quality and reduction in the control signal commutations. This paper presents all these ideas applied to the greenhouse climate control problem.

Robust Pressure Control in a Mobile Robot for Spraying Tasks

This article presents a robust control system aimed at regulating the output pressure of a spraying system mounted on a mobile robot for fumigation tasks despite changes in the vehicle velocity; that is, the pressure setpoints are calculated based on the actual velocity of the vehicle at each sampling time and on a predefined volume of pesticides to apply based on the crop growth state, and are then used in a feedback loop for pressure control purposes, where the controller accounts for uncertainty in the system. This article focuses on the dynamic modeling of the spraying system based on the reaction curve method (analysis of the response to open loop steps) and the development and test of a robust control strategy to achieve the desired pressure profile. Quantitative feedback theory has been used as a robust control technique to cope with system uncertainties and to improve the gain-scheduling strategy used in previous works. Illustrative results are shown and commented.