Abstract

Abstract
This paper describes the application of a Brain Emotional Learning (BEL) controller to improve the response of a SDOF structural system under an earthquake excitation using a magnetorheological (MR) damper. The main goal is to study the performance of a BEL based semi-active control system to generate the control signal for a MR damper. The proposed approach consists of a two controllers: a primary controller based on a BEL algorithm that determines the desired damping force from the system response and a secondary controller that modifies the input current to the MR damper to generate a reference damping force. A parametric model of the damper is used to predict the damping force based on the piston motion and also the current input. A Simulink model of the structural system is developed to analyze the effectiveness of the semi-active controller. Finally, the numerical results are presented and discussed. © Springer International Publishing Switzerland 2017.

Abstract
At the present there is a high pressure toward the improvement of all production processes. Those improvements can target distinct factors along the production chain. In particular, and due to recent tight energy efficiency policies, those that involve energy efficiency. As can be expected, agricultural processes are not immune to this tendency. Even more when dealing with indoor productions. In this context, this work presents an innovative system that aims to improve the energy efficiency of a trees growing platform. This improvement in energy consumption is accomplished by replacing an electric heating system by one based on thermodynamic panels. The assessment of the heating fluid caudal and its temperature was experimentally obtained by means of a custom made scaled prototype whose actuators status are commanded by a Fuzzy-based controller. The obtained results suggest that the change in the heating paradigm will lead to overall savings that can easily reach 60% on the energy bill. © Springer International Publishing Switzerland 2017.

Abstract
Vehicle suspension systems are usually based on passive actuators and control modes in which the damping and stiffness parameters are predefined and kept constant for all road profiles and vehicle response. A different approach is to use active systems to monitor and control the suspension motion in order to improve the vehicle handling and comfort. However, these systems have a complex design requiring a relatively high power source to operate. Semi-active systems are also capable to modify the properties of the vehicle suspension but with low power requirements making them a promising technology for demanding vibration control systems. This paper presents the findings of a numerical simulation involving a simplified model of a vehicle suspension system equipped with a MR actuator. The system is designed to improve the behavior (comfort and handling) of the vehicle compared with a traditional passive suspension system. A simple fuzzy logic controller is used to decide the control action in accordance with the measured system response. © Springer International Publishing Switzerland 2017.

Abstract
This work describes an experimental setup that was developed in order to automate the One-dimensional consolidation properties of soil test. This experimental setup assures repeatability in the data acquisition test, avoiding human errors. The described setup is based on LabVIEW, LVDT sensors, a 16 Bit Data Acquisition Board, a Load device and a Consolidometer. The experimental setup was developed according to the standard ASTM D2435 / D2435M - 11.

Abstract
This paper aims to evaluate the performance of a semi-active controlled suspension system using a magneto-rheological (MR) damper to provide better ride comfort and safety to vehicle passengers than an uncontrolled or passive suspension system. Passive systems represent a conventional solution for vibration control of suspension systems. Although this system is a proven, reliable and economic technology, their parameters cannot be modified according to the road conditions. On the other hand, active systems allow a continuous control of the suspension motion, but require a complex and energy demanding actuator. The proposed suspension system has the adaptability of active systems with lower energy consumption, which constitute an economic and efficient option for vibration control in vehicle suspensions. The analysis was carried out with a set of numerical simulations in Matlab/Simulink using a 1/4 vehicle suspension model with two degrees of freedom for a passive system and two semiactive control modes based on fuzzy and optimal controllers.