This paper presents the design and validation of a custom temperature control board tailored for Skipper-CCD sensors that are adaptable to diverse experimental configurations. The board features two galvanically isolated sections: a control section incorporating a Raspberry Pi and essential instrumentation components for measurements and board protections and a power section housing the buck converter with corresponding instrumentation components for enhanced protections and measurements. The seamless integration of these sections ensures robust temperature regulation while providing comprehensive safeguards against potential anomalies. Through meticulous design and rigorous experimental validation, the proposed temperature control board offers reliable and precise thermal management tailored to the specific requirements of Skipper-CCD sensors. Illustrated by its application in the OSCURA experiment, this board is a case example, demonstrating its potential extension to other applications.

Multiphase electric drive systems, which consist of power electronic converters and multiphase machines (with n greater than 3), have become a reliable solution for various high-power industrial needs, including propulsion systems for electric ships, vehicles and renewable energy applications, due to their phase redundancy. However, fully exploiting their inherent benefits requires more sophisticated control techniques. The finite control set model predictive control has emerged as a suitable strategy due to its ease of implementation and applicability across different systems. Nevertheless, tuning the weighting factor in the cost function significantly impacts control outcomes, making it an important aspect to consider. In this context, novel control techniques named Sequential Model Predictive Control (SMPTC) and Sequential Model Predictive Control based on Virtual Vectors (SMPTC-VV) have emerged as viable alternatives. Both methods eliminate weighting factors by using simple cost functions applied sequentially. SMPTC-VV integrates virtual vectors to reduce the secondary-plane currents, decreasing vibrations in induction machines. Despite the recent introduction of SMPTC and SMPTC-VV strategies, studies comparing the performance of these controllers have not yet been conducted. Therefore, this article presents a comparative study of these control techniques.

Power electronic converters play a pivotal role in integrating renewable energy sources into the grid or standalone electrical power systems by converting and conditioning the generated power, achieving a sustainable future and reducing greenhouse gas emissions. This paper focuses on implementing an asymmetrical cascaded H-bridge multilevel power converter with hybrid modulation for on-grid solar photovoltaic generation systems. Specifically, this paper introduces a predictive current control and reactive power compensation capability. The paper evaluates the efficiency of the proposed system in terms of generated energy quality and the effectiveness of the predictive control strategy.

This paper studied the design of a predictive current control strategy with fault tolerance and reactive power minimization applied to a multi-modular topology based on indirect 2-level matrix converters fed by a six-phase generator. The control algorithm of the proposed strategy involves coupled current signals to perform error compensation between the converter modules, aiming to address potential system faults while maintaining reactive power close to zero. The results, obtained through simulation, were evaluated considering each module’s input and output currents and the final load current, as well as reactive power minimization, incorporating the obtained values of total harmonic distortion and mean squared error. The behaviour was analyzed in steady-state and transient conditions, with the system operating nominally and under fault conditions. The results demonstrate the effectiveness and good performance of the proposed strategy with the utilized topology, achieving a satisfactory response to faults through compensation and constant reactive power minimization.

A predictive current control design for a multi-modular indirect matrix converter using a three-level neutral-point clamped for the inverter side is studied. The multi-modular topology is based on two 3-Level Indirect Matrix Converter modules, and the control strategy proposal involves a single model-based predictive current control and the use of a coupled current signal. It is the interaction between the two three-phase output current of each module for error compensation between these, along with the ability to operate in failures. This article shows the results of the simulation in Matlab/Simulink of the 3-level multi-modular indirect matrix converter with coupled control, compared with an independent control for each module of the converter, in order to verify the performance obtained in terms of total harmonic distortion and mean square error. In addition, the analysis was carried out with respect to the behavior in transient, stationary state and with simulated failures for each module. The results obtained support the effectiveness of the control strategy with the proposed topology showing, with the control coupled, a decrease in the mean square error in the current signal of the final load, having a good value of total harmonic distortion and the capacity for optimal operation in the event of failures of the generation or conversion system.

Presentación realizada en el marco Proyecto PINV18-765: Vehículos aéreos no tripulados en aplicaciones para la agricultura de precisión para el monitoreo de cultivos agrícolas. Cuyo objetivo general fue: el Estudio, investigación, análisis y validación experimental de, por un lado, avanzadas estrategias de control de vuelo de vehículos no tripulados (UAV) y, por otro, de algoritmos de procesamiento de imágenes obtenidas por el UAV, orientada al análisis de cultivos agrícolas enfocado al desarrollo del sector agropecuario.

In this paper, three sliding-mode-based control techniques for position and attitude tracking trajectory for a quad-rotor unmanned aerial vehicle (UAV) are evaluated regarding the tracking performance and the chattering in the motors’ speed. The evaluation is made through numerical simulations of a stationary flight and waypoint tracking with disturbances. The results show that Sliding Mode controllers are suitable for UAV applications, with high tracking performance, particularly sliding mode controllers with exponential reaching law. The modified super twisting algorithm can achieve the control objectives with a notable reduction in the chattering effect.

This work investigates the problem of finite-time position and attitude trajectory of quadrotor unmanned aerial vehicle systems based on a modified second order sliding mode algorithm. The selected algorithm is a modified super-twisting with both nonlinear and linear correction terms.

In this work, a time delay estimation based optimal conventional and second order sliding mode stator currents controller are proposed and compared for a six-phase induction machine fed by voltage source power converters. In a first step, the speed is regulated in an outer loop using a proportional-integral controller. Then, in a second step, the stator currents are controlled in an inner loop using the proposed methods. On one hand, the first method is a combination of time delay estimation with optimal first order sliding mode with exponential reaching law. On the other hand, the second method is a combination of time delay estimation with optimal super-twisting control. Based on Lyapunov theory, the stability of the stator currents closed-loop error dynamics is demonstrated and sufficient conditions of stability are determinate. As a case example, numerical simulations have been conducted on an asymmetrical six-phase induction machine to demonstrate the good features of the developed nonlinear controllers.

This paper investigates the problem of stator current control in presence of uncertainties and unmeasurable rotor current for a six-phase induction motor drive. An inner control loop based on a robust discrete-time sliding mode with time delay estimation method is proposed to ensure the finite-time convergence of the stator currents to their desired references while the proportional-integral controller is used for the outer speed control. Sufficient conditions are established to ensure the stability of the closed-loop system. Simulation results were carried out to verify the performance of the proposed robust control strategy for a six-phase induction motor drive.

There are several control techniques for active power filter applications. This paper presents a new alternative of predictive current control for a cascade H-bridge multilevel converter, where the optimal vector selected by the predictive controller is used for a modulation stage to obtain a fixed switching frequency. Simulation results validate the proposal where almost similar results can be obtained in comparison with the traditional methods.

The interest in electricity generation from photovoltaic (PV) systems has experienced significant growth in recent years, justified by the reduced environmental impact generated. The energy extracted from PV systems is related to the amount solar irradiation and thus the angle of incidence of the sun's rays on the surface of the panels. This paper presents, on one hand, a novel design of a biaxial solar tracking system (azimuth and elevation angle) for PV power application and on the other, the set-up of the control system focused on increasing the efficiency of the PV generation system across the implementing of a digital Proportional-Integral-Derivative (PID) position control scheme to achieve the maximum power point tracking (MPPT), ensuring the maximum energy available from the photovoltaic panels.

This article considers the speed control of asymmetrical dual three-phase generator by using an inner loop of Model Based Predictive Control (MBPC) to predict the effects of future control actions on the state variables. In order to achieve this goal, the algorithm uses both a Luenberger Observer and a Kalman Filter with the purpose of estimating the rotor currents. Thereafter, the speed control is used to reach the Maximum Power Point Tracking (MPPT), which ensures that it is delivered to the load. Finally, a comparison of the efficiency of the MBPC when considering the rotor current estimators and when they are used an estimator based on the state space representation.

Most sensorless algorithms applied to electrical drives are based on the mathematical representation of a physical system which includes electrical and mechanical variables of the motor. However, in electrical drive applications, the rotor current cannot be measured, so it must be estimated. This paper deals with the speed sensorless control of asymmetrical dual three-phase induction machines by using an inner loop of Model-Based Predictive Control (MBPC). The MBPC is obtained from the mathematical model of the machine, using a state-space representation where the two state variables are the stator and rotor currents, respectively. The rotor current is estimated using a reduced order estimator based on a Luenberger observer. Finally, simulation results are provided to show the efficiency of the proposed sensorless speed control algorithm.