Discharge Coefficients for Sluice Gates Set in Weirs at Different Upstream Wall Inclinations

Laboratory experiments and numerical simulations are performed to measure discharge coefficients in the case of a gate located on the upstream wall of a weir for flood storage. The effect of the gate slope and the side contraction have been taken into account. The study was first performed experimentally, when three series of tests were carried out with (and without) a broad crested weir located under the gate, at different values of the inclination angle of the weir upstream wall, and at different values of the shape ratio and the relative opening. In order to provide useful suggestions for those involved in sluice gate construction and management, three equations were obtained based on multiple regression, relating the discharge coefficient to different parameters that characterize the phenomenon at hand, separating the case when the broad-crested weir was present. Then numerical simulations were executed by means of the Reynolds-averaged Navier–Stokes (RANS) equations with the k-ε turbulence closure model and in conjunction with the volume of fluid (VOF) method, to validate the numerical results against the experimental and to possibly investigate phenomena not caught by the experimental measurements. Simulated discharges were very close to the observed ones showing that the proposed three-dimensional numerical procedure is a favorable option to correctly reproduce the phenomenon

Dinamiche dei popolamenti del pino d'Aleppo negli alvei delle fiumare dell'Alto Ionio cosentino

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Robust Disturbance Rejection Control of DC/DC Interleaved Boost Converters with Additional Sliding Mode Component

Interleaved DC/DC boost converters are nowadays widely studied due to their properties of reducing the current ripple and increasing fault tolerance. This paper describes a control method that allows good output voltage regulation, together with robustness against parameter uncertainties, deviation of the supply voltage of the source, and load deviation. These objectives are obtained by determining an equivalent circuital scheme of the interleaved boost and associating to this scheme a linear mathematical model by means of the exact linearization method. Subsequently, trajectory tracking control techniques are employed based on disturbance compensation and a sliding mode component is added to cope with parameter uncertainties and possible compensation errors. The controller, applied to the above equivalent conventional boost model, allows to command the duty cycle of single phases of the Mosfets. This controller uses the output voltage and the currents flowing in the phases of the converter as feedback variables. Simulation results show the validity of the proposed approach

GA-Based Off-Line Parameter Estimation of the Induction Motor Model Including Magnetic Saturation and Iron Losses

This paper, starting from recent papers in the scientific literature dealing with Induction Motor (IM) dynamic modelling, as a first step, improves its space-vector dynamic model, including both the magnetic saturation and iron losses; particularly it takes into account the dependence of the magnetic saturation by the stator leakage inductance, as a further effect of the load. Afterwards, it proposes an off-line technique for the estimation of electrical parameters of this model, which is based on Genetic Algorithms (GA). The proposed method is based on input-output measurements and needs neither the machine design geometrical data nor a FEA of the machine. It focuses on the application of an algorithm based on the minimization of a suitable cost function depending on the stator current error. The proposed electrical parameters estimation method has been initially tested in numerical simulation and further verified experimentally on a suitably developed test set-up

An adaptive multi-rate system for visual tracking in augmented reality applications

The visual tracking of an object is a well-known problem, and it involves many fields of applications. Often a single sensor, the camera, could not provide enough information in order to track the whole object trajectory due to a low updating rate; therefore a multi-sensor system, based also on inertial measurements, could be necessary to improve the tracking accuracy. This leads to the fundamental question: how can information from different sensors be combined when they work at different rates? In this paper an approach based on recursive parameter estimation focusing on multi-rate situations is suggested. The problem is here formulated as the state-of-the-art problem of the visual tracking of an object in augmented reality environments. The multi-sensor system consists of a webcam and a 3-axis MEMS inertial sensor both with different sample rates. The augmented reality application has been designed for the object detection problem, and it has been tested experimentally in a suitably developed test set-up

Descriptor-type Robust Kalman Filter and Neural Adaptive Speed Estimation Scheme for Sensorless Control of Induction Motor Drive Systems

This paper deals with robust estimation of speed and rotor flux for sensorless control of motion control systems which use induction motors as actuators. Due to the observability lack of five and six order Extended Kalman Filters, speed is here estimated by means of a Total Least Square algorithm with Neural Adaptive mechanism. This allows the use of a fourth-order Kalman Filter for estimating rotor flux and to filter stator currents. To cope with motor-load parameter variations, a descriptor-type robust Kalman Filter is designed taking explicitly into account these variations. The descriptor-type structure allows direct translation of parameter variations into variations of the coefficients appearing in the model. This, in turn, brings to some simplifications in the design of the filter. Simulation experiments are shown with the aim of verifying the goodness of the whole estimator

Sensorless Control of Induction Motor Drive Based on Robust Kalman Filter and Adaptive Speed Estimation

This study deals with robust estimation of rotor flux and speed for sensorless control of motion control systems with an induction motor. Instead of using sixth order extended Kalman filters, rotor flux is estimated by means of a fourth order descriptor-type robust Kalman filter which explicitly takes into account motor parameter uncertainties, whereas the speed is estimated using a recursive least-squares algorithm starting from the knowledge of the rotor flux itself. It is shown that the descriptor-type structure allows for a direct translation of parameter uncertainties into variations of the coefficients appearing in the model, and this improves the degree of robustness of the estimates. Experimental findings, carried out on a closed loop system consisting of a low power induction motor-load system, a PI-type controller and the proposed estimator, are shown with the aim of verifying the goodness of the whole closed loop control system

Hybrid Observer for Indoor Localization with Random Time-of-Arrival Measurments

In this work an indoor position estimation algorithm will be proposed. The position will be measured by means of a sensor network composed by fixed beacons placed on the indoor environment and a mobile beacon mounted on the object to be tracked. The mobile beacon communicates with all the fixed beacons by means of ultra wide-band signals, and the distance between them is computed by means of time of flight techniques. Moreover, inertial measurements will be used when the position measurements are not available. Two main problems will be considered in the proposed architecture: the fact that the beacons work with a lower update rate than the IMU, and that the mobile beacon can comunicate with only one fixed beacon at a time. Experimental results will be shown in order to validate the effectiveness of the proposed technique