F. Capraro

Hybrid Control of a Supermarket Refrigeration Systems

This paper presents a non-linear model predictive control (NMPC) of a supermarket refrigeration system. This is a hybrid process involving switching nonlinear dynamics and discrete events, on/off manipulated variables, like valves and compressors, continuous controlled variables like goods temperatures and finally, several operation constraints. The hybrid controller is based on a parameterization of the on/off control signals in terms of time of occurrence of events instead of using directly binary values, on this way, we can reformulate the optimization problem as a NLP problem. A rigorous model of a real supermarket refrigeration system provided by Danfoss is presented as well as results of the hybrid controller operating on it. The paper describes the hybrid process, presents the control problem formulation and provides some results of the proposed approach and comparisons with the traditional control.

Neural Network-Based Irrigation Control for Precision Agriculture

In the present work, a design of an automatic irrigation neuro-controller for precision agriculture is presented. The irrigation neuro-controller regulates the level of moisture in agricultural soils, specifically in the root zone, using an on-off control-type that opens and closes the valves of the irrigation system (IS). The changes in the moisture levels in the roots area can be modeled as a non-linear differential function depending mainly on the amount of water supplied by the IS, the crop consumption, and the soil characteristics. This dynamic model is identified by a neural network (NN). After the NN is trained, it is used as a prediction model within the control algorithm, which determines the irrigation time necessary to take the moisture level up to a user desired level. At the same time, the NN is re-trained in order to get a new and improved model of the moistures soils, giving to the IS the capability of adapt to the changing soil characteristics and water crop needs. In this work, it is also presented the main advantages of using this irrigation closed-loop adaptive controller instead of traditional systems that operates to open-loop, such as timed irrigation control.

Logic Embedded NMPC of a Solar Air Conditioning Plant

This paper presents a hybrid controller for a solar air conditioning plant, located at the University of Seville, Spain, and used as a benchmark for the HYCON NoE of the European Union (EU). The plant uses two sources of energy: solar and gas, plus a set of accumulation tanks and an absorption tower to provide conditioned air to a university building. The hybrid character comes from the discrete decisions that have to be taken in relation with the energy source in use, which is selected by means of on/off valves, plus the continuous nature of the process and other manipulated variables. The control aim is to operate the conditioned air system using the smaller possible amount of energy from gas and maintaining other variables close to their set points. The hybrid control is based on a model predictive control strategy developed with the objective of dealing with the mixed discrete-continuous nature of the process in an efficient way. A novel approach incorporating an internal model with embedded logic control is used to transform the hybrid problem in a continuous-nonlinear one where NMPC can be applied. The paper presents results obtained both, in simulation and in the real system.

Intelligent Irrigation in Grapevines: A Way to Obtain Different Wine Characteristics

This work presents the field implementation of an intelligent irrigation controller, applied to grapevine crops. The proposed irrigation system includes the moisture measurements and the development of an intelligent control system, in order to maintain the moisture level around a set value. Moisture reference value for different irrigation treatments, such as water stress or field capacity, is decided by the user according to the desired enological grape quality. This technology is an appropriate tool for crops managing and, in addition helps to overcome difficulties imposed by a growing water demand and to reduce extraction costs.

HYBRID PREDICTIVE CONTROL OF A SOLAR AIR CONDITIONING PLANT

This paper presents a hybrid controller for a solar air conditioning plant, located at the University of Seville, Spain, and used as a benchmark for the HYCON NoE of the EU. The plant uses two sources of energy: solar and gas, plus a set of accumulation tanks and an absorption tower to provide conditioned air to an university building. The hybrid control is based on a model predictive control strategy developed with the objective of operating the air conditioning system using the smaller amount of energy from gas. A novel approach incorporating an internal model with embedded logic control is used to transform the hybrid problem in a continuous-nonlinear one. Simulation results are presented, showing promising results.

Laboratorio Virtual y Remoto para Simular, Monitorizar y Controlar un Sistema de Riego por Goteo en Olivos

This article presents the development and application of a laboratory designed for simulating control an irrigation strategies that can be then applied in field, in a drip irrigation system installed in a pilot plant. The system presented in this work involves the development of a simulation software, the monitoring of different variables, and the remote control of a pilot plant. This article also describes other components of the system, such as the moisture sensor network, the communication network, and the remainder hardware required for the remote control. The laboratory as well as the pilot plant is installed in olive groves located in the province of San Juan, Argentina.

Control of a production-inventory system using a PID controller and demand prediction

Abstract A common and important problem in business is the determination of inventory policies for a production system within a changing business environment and market demand. In this paper, an automatic pipeline feedback order-based production control system (APIOBPCS), considering a demand with cyclic and stochastic components, is proposed. The dynamics and delays of the production process are modeled as a pure delay. The control system structure consists of a PID (Proportional, Integrative and Derivative) controller with an Extended Kalman Filter-based demand prediction. The main objective of the this dynamic controller is to stabilize and regulate the inventory levels in function of a desired set-point level. The Extended Kalman Filter (EKF) estimates the parameters of a Volterra time-series model to forecast future values of the demand. A control error analysis is also performed for the proposed inventory control system, in order to obtain bounds for the control errors and to probe its stability. This methodology is useful to make an appropriate decision about the desired inventory level for a given demand prediction error. The inventory control system is evaluated by simulations showing a good performance.

Use of site-specific measurement stations for irrigation management and crops water demand monitoring. An experience in almonds, in the province of San Juan, Argentina

In the context of modern agriculture, it is important for farmers and agricultural consultants to count with technological tools that allow an appropriate monitoring of the development of the crop, and of the water and fertilizers applied among other. These objectives can be achieved if information of the soil-water-crop-atmosphere complex system is organized and on-line available for the users. This work describes our experience during the installation and set up in field of a group of measurement stations, intended to give site-specific information regarding what is going inside the crop. Each station measures the ambient temperature and humidity at four different heights, the atmospheric pressure, the solar radiation index, wind velocity and direction, crop temperature, trunk growth, soil moisture at four depths, soil temperature, amount of water supplied, and pressure and caudal in the pipes. Information is saved, at regular intervals, in a data logger, and then transmitted to a PC located in an office. The system is complemented with a PLC-based irrigation controller that allows to automatically performing the irrigation schedule. The experience was realized in a young almonds crop, located in the province of San Juan. It is expected to use this system along the 2015/2016 season in order to determine the crop coefficient (Kc) in four almond varieties and verify the effects of applying regulated deficit irrigation (RDF) treatments.

Approximate dynamic programming based controller for a production-inventory system

This article presents the design and development of a control system based on Approximate Dynamic Programming, applied to a particular case of a single echelon, single product production inventory-system. The structure presented in this work allows to find an approximate solution to the optimal control problem. The developed controller is feasible to be implemented in real-time mode. In addition it also allows to manage dynamic variations in the process to be controlled. Theoretical results are obtained and compared to a classical LQR controller. Simulation experiments showed the good performance and the feasibility of the proposed structure.