This article presents on controlling a fishmeal dryer. A model-based predictive controller was designed to control the amount of moisture present in fishmeal. The Nonlinear Extended Prediction Self-Adaptive Control (NEPSAC) approach has been used. This approach uses a non-linear model in its implementation. In this work we study the use of piecewise affine (PWA) models to approximate the non-linear model. The use of PWA models reduces calculation time but worsens the performance of the controller. © 2020 IEEE.

One of the main problems organic banana crops is the presence of pests, affecting crop yield, post-harvest and export fruit quality. In Piura (Peru), pests with the greatest presence are Thrips, Squamas, Black Weevil, etc. This article describes the development of a prediction model, based on a supervised machine learning algorithm: Logistic Regression and Support Vector Machine, which will estimate the future level of incidence (low and medium) of a specific pest. The model was designed including the input data (climate) that were obtained from a network of IoT sensors in-situ in the banana crop, and output data (level of incidence) that was collected with manual record and visual inspection. The model developed can predict pest incidence at 79% accuracy (with test data). These first results show feasibility to estimate in advance the incidence of pests in that crop. Future implementati...

This paper presents a methodology for the design and the implementation of a PID (Proportional-Integral-Derivative) using IMC (Internal Model Control) tuning method by means of experiments performed on organic banana. In this work, the parameters of the linear and nonlinear model of a cooling chamber for fruits are identified. Simulation studies and implementation of the PID-IMC closed-loop control system demonstrate that energy saving were obtained of the order of 20% with respect to the entire system. © 2020 IEEE.

J. Manrique thanks the financial support of the Proyecto Concytec - Banco Mundial, through its executing unit Fondo Nacional de Desarrollo Científico, Tecnológico y de Innovación Tecnológica (Fondecyt), for its research work Dynamic Modeling and Validation of a Refrigeration System and Cold Room for Fruit Preservation..

In the northern region of Peru, the agro-export sector has grown considerably in the last ten years. In Piura specifically, it can be seen a huge expansion in products such as grape, mango and banana. Cooling systems are important for the agro-export sector representing between 40 and 50% of total electricity consumption, so it is necessary to have efficient automated cooling systems that would meet high quality and performance standards.In this article, a model based on transfer function has been identified for the refrigeration pilot plant of the University of Piura and a PI controller has been designed for said model, comparing its performance in relation to the ON OFF controllers currently used in the Peruvian agro-industry. The control variable was the compressor frequency and the controlled variable was the internal temperature of the cold-room.The refrigeration pilot plant of the ...

Many automotive systems such as engines have manufacturing tolerances or change over time. This limits the performance of controllers tuned for the nominal case. A robust controller can not always overcome this performance gap. Against this background, in this work, we propose a self-tuning control strategy for an engine air path model obtained from data of a real engine and show its benefits setting. The self-tuning control consists of an online parameter estimation algorithm for polynomial non-linear autoregressive with exogenous input (PNARX) models and a nonlinear model predictive controller (NMPC) implemented by the continuation/generalized minimum residual (C/GMRES) algorithm. In a first step design of experiments (DOE) is utilized to identify a PNARX model offline from measurements performed on an engine test bed. A tracking NMPC is designed for this model and applied in simulatio...

The contamination of soils by heavy metals is a current problem for agricultural production. Rapid access and reliability to heavy metal concentration such as cadmium is crucial for international trade. In the present study, visible and near infrared (VIS-NIR) spectroscopy, combined with linear and statistical methods, were used to predict the cadmium concentration of organic cocoa bean samples. Partial Least Square Regression (PLSR) and Support Vector Regression (SVR) were implemented to estimate the content of this heavy metal from hyperspectral imaging and chemical analysis. Competitive Adaptive Reweighted Sampling Method (CARS) and Jackknife method were used for selecting optimal wavelength. The SVR model performed satisfactorily with the use of 45 resulting wavelengths from optimization using CARS and the Jackknife method, with an adjusted coefficient for the test R2 of 0.9401 and a...

This article summarizes our investigation about technologies for moisture sensing, a parameter of analysis and study over many years because it serves to estimate the quality, and performance at commercial and environmental level. This paper presents some contributions. First, we developed a new classification about the most representative system in research and scientific articles. We shows applications of the technology in recent years according to the consulted articles. Also, we expose systems for soil and vegetation moisture measurement, this is an important application in this decade because helps to agriculture and many control applications (forestall fires, earthquakes, etc.). Finally, the tendency about new investigations is presented. This paper is important for microwave sensors designers and investigators in moisture control, because they will have a reference about what kind...