HighlightsControl theory applied to precision irrigation reduces water consumption and improves crop productivity.A model-based control using hybrid automata is proposed to describe soil, crop, and weather dynamics.The model was developed and validated with experimental data from a grass irrigation process.The proposed model can be used to develop robust and real-time control algorithms to improve irrigation systems. Abstract. Closed-loop control for precision irrigation represents an effective method to provide water savings in this resource-intensive activity. Typically, implementation of these systems uses an on-off control approach with soil moisture as the feedback variable. In these cases, no process modeling is required due to the simplicity of the implemented control algorithm. However, the amount of water consumed by irrigation globally presents an interesting application area for the control discipline. Therefore, to obtain greater water savings and to improve crop productivity through control theory, an irrigation model is required that integrates the three main elements in the irrigation process: soil, crop, and weather. This article proposes a hybrid automata model for a closed-loop irrigation system applied to a grass-covered area. The main measured variables used to represent the process dynamics are soil moisture, vegetation index, and evapotranspiration. The hybrid automata approach allows a complex system to be modeled as a finite state machine in which there is a specific linear model for each state. When certain conditions are met, the system transitions from one state to another, and the new behavior is represented by a different linear model. To develop the proposed model, experimental data were obtained from an irrigation process, the data were analyzed to produce a model using the hybrid automata approach, and finally the model was validated with a new set of measured data. Keywords: Closed-loop irrigation, Evapotranspiration, Hybrid automata, NDVI, Precision irrigation modeling.

In smart farming, precision agriculture irrigation is essential to reduce water consumption and produce higher crop yields. Closed-loop irrigation based on soil moisture measurements has demonstrated the capability to achieve a considerable amount of water savings while growing healthy crops. Automated irrigation systems are typically implemented over wireless sensor networks, where the sensing devices are battery-powered, and thus they have to manage energy constraints by implementing efficient communication schemas. Self-triggered control is an aperiodic sampling strategy capable of reducing the number of networked messages compared to traditional periodical sampling. In this paper, we propose an energy-efficient communication strategy for closed-loop control irrigation, implemented over a wireless sensor network, where event-driven soil moisture measurements are conducted by the sensing devices only when needed. Thereby, the self-triggered algorithm estimates the occurrence of the next sampling period based on the process dynamics. The proposed strategy was evaluated in a pecan crop field and compared with periodical sampling implementations. The experimental results show that the proposed adaptive sampling rate technique decreased the number of communication messages more than 85% and reduced power consumption up to 20%, while still accomplishing the system control objectives in terms of the irrigation efficiency and water consumption.

Remote Handling (RH) systems are now frequently used to conduct inspections and maintenance in hazardous environments. New particle accelerator facilities present unique logistic challenges due to high radiation levels, a hazardous environment and heavy loads. The Facility for Antiproton and Ion Research (FAIR) will deliver a beam of all ions up to uranium with intensities up to 10 12 238 U ions/s, which will cause high levels of radiation during operation so human access is limited. This paper contains a survey on RH logistics for existing High Intensity Beam (HIB) facilities to determine state of the art RH practices and to draw a conclusion based on the analysis. The second part of this paper presents a detailed study of beam losses, the radiation environment, RH logistic challenges and some proposed solutions for Super-FRS. This paper will also suggest a Systems Engineering (SE) approach for developing Super-FRS RH logistics.

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The Super-FRS, Superconducting Fragment Separator, is a unique machine that presents several challenging technical problems. One of these is regarding how to conduct maintenance in the target area where high levels of radiation will be generated and human access is forbidden. To address this problem the use of a remote maintenance system is foreseen. The objective of this paper is to develop a systems engineering (SE) research and development (R&D) approach suitable to develop the Super-FRS Target Area Remote Maintenance Systems (TARMS) and the RH design adaptation of the components in the target area. The Super-FRS target area is described in detail in order to introduce the need for a remote maintenance system. Components in the target area are classified by adopting ITER RH maintenance classification. The general scenario of remote handling and the current target area remote maintenance system are described. Finally, the proposed systems engineering approach is presented.