Dynamic Sliding Mode Control of DC-DC Converter to Extract the Maximum Power of Photovoltaic System Using Dual Sliding Observer

This paper concerns the maximum power extraction of a photovoltaic generator system (PGS). The PGS consists of single photovoltaic (PV) cells. To improve the efficiency of a PGS, it is necessary to work within its maximum power point (MPP). In a PGS, output power is dependent on solar irradiance and the operating temperature and, therefore, MPP would be varied. To address this problem, a converter should be placed after the PGS and a smooth control signal should be used to adjust its duty cycle. The other challenge of a total system, i.e., PGS and converter, is the uncertainty involved. To overcome this uncertainty, a dynamic sliding mode control (SMC) can be used to regulate the smooth duty cycle. The low-pass integrator before the system can remove the chattering in dynamic SMC. However, due to the integrator, the states of the system increase and, hence, we propose a dual sliding observer (DSO) to estimate this added state. For a reliable comparison with the conventional SMC, the same proposed DSO can be applied in both dynamic and conventional SMC. The provided comparison shows the effectiveness of dynamic SMC in chattering suppression and real implementation with respect to conventional SMC

Higher Order Sliding Mode Control of MIMO Induction Motors: A New Adaptive Approach

In this paper the objective is to force the outputs of nonlinear nonaffine multi-input multi-output (MIMO) systems to track those of a linear system with the desired properties. The approach is based on designing higher order sliding mode controller (HOSMC) with the definition of a new proportional-integral (PI) sliding surface. To this end, a linear state feedback with an adaptive switching gain (ASG) is applied to the nonlinear MIMO systems. Therefore, the switching gain can increase or decrease based on the system conditions. Then, the chattering is completely removed using a combination of HOSMC and ASG. Moreover, the proposed procedure is independent from the upper bound of the matched uncertainty, which is in the direction of system inputs. The finite time convergence to the sliding surface is also proved, which provides an invariance property in finite time. Note that invariance is the most important property of SMC. Finally, the general model of MIMO induction motors (IM) is used to address and to verify the proposed controller.The authors wish to express their gratitude to the Basque Government, through the project EKOHEGAZ II (ELKARTEK KK-2023/00051), to the Diputación Foral de Álava (DFA), through the project CONAVANTER, to the UPV/EHU, through the project GIU20/063, and to the MobilityLab Foundation (CONV23/14. Proy. 16) for supporting this work

A Real-Time Implementation of Novel and Stable Variable Step Size MPPT

This paper presents a complete study of a standalone photovoltaic (PV) system including a maximum power tracker (MPPT) driving a DC boost converter to feed a resistive load. Here, a new MPPT approach using a modification on the original perturb and observe (P&O) algorithm is proposed; the improved algorithm is founded on a variable step size (VSZ). This novel algorithm is realized and efficiently implemented in the PV system. The proposed VSZ algorithm is compared both in simulation and in real time to the P&O algorithm. The stability analysis for the VSZ algorithm is performed using Lyapunov’s stability theory. In this paper, a detailed study and explanation of the modified P&O MPPT controller is presented to ensure high PV system performance. The proposed algorithm is practically implemented using a DSP1104 for real-time testing. Significant results are achieved, proving the validity of the proposed PV system control scheme. The obtained results show that the proposed VSZ succeeds at harvesting the maximum power point (MPP), as the amount of harvested power using VSZ is three times greater than the power extracted without the tracking algorithm. The VSZ reveals improved performance compared to the conventional P&O algorithm in term of dynamic response, signal quality and stability

Implementation of a Cascade Fault Tolerant Control and Fault Diagnosis Design for a Modular Power Supply

The main objective of this research work was to develop reliable and intelligent power sources for the future. To achieve this objective, a modular stand-alone solar energy-based direct current (DC) power supply was designed and implemented. The converter topology used is a two-stage interleaved boost converter, which is monitored in closed loop. The diagnosis method is based on analytic redundancy relations (ARRs) deduced from the bond graph (BG) model, which can be used to detect the failures of power switches, sensors, and discrete components such as the output capacitor. The proposed supervision scheme including a passive fault-tolerant cascade proportional integral sliding mode control (PI-SMC) for the two-stage boost converter connected to a solar panel is suitable for real applications. Most model-based diagnosis approaches for power converters typically deal with open circuit and short circuit faults, but the proposed method offers the advantage of detecting the failures of other vital components. Practical experiments on a newly designed and constructed prototype, along with simulations under PSIM software, confirm the efficiency of the control scheme and the successful recovery of a faulty stage by manual isolation. In future work, the automation of this reconfiguration task could be based on the successful simulation results of the diagnosis method.This research was funded by the Tunisian Ministry of Higher Education and Scientific Research

A global integral terminal sliding mode control based on a novel reaching law for a proton exchange membrane fuel cell system

Proton exchange membrane fuel cells are devices with huge potential for renewable and clean industries due to their high efficiency and low emissions. Since the proton exchange membrane fuel cell employed in this research supplied a low output voltage, it was encouraged to use a boost converter with a designed non-linear controller to provide a suitable end-user voltage. In this paper, we proposed a novel control framework based on sliding mode control, which is a global integral sliding mode control linked with a quick reaching law that has been implemented in a commercial fuel cell system Heliocentris FC50 through a dSpace 1102 control board. We compared the strategy with a conventional sliding mode controller and an integral terminal sliding mode controller where we addressed a Lyapunov stability proof has for each structure. We contrasted the experimental outcomes where we proved the superiority of the proposed novel design in terms of robustness, convergence speed. Additionally, as the sliding mode controllers are well known by the energy consumption caused by the chattering effect, we analysed every framework in these terms. Finally, it was found that the proposed structure offered an enhancement in the energy consumption issues. Moreover, the applicability of the proposed control scheme has been demonstrated through the real time implementation over a commercial fuel cell.The authors wish to express their gratitude to the Basque Govern-ment, through the project EKOHEGAZ (ELKARTEK KK-2021/00092) , to the Diputacion Foral de alava (DFA) , through the project CONA-VANTER, and to the UPV/EHU, through the project GIU20/063, for supporting this work. The authors wish to express their gratitude to the Basque Govern-ment, through the project EKOHEGAZ (ELKARTEK KK-2021/00092) , to the Diputacion Foral de alava (DFA) , through the project CONA-VANTER, and to the UPV/EHU, through the project GIU20/063, for supporting this work

Experimental validation of fuzzy type-2 against type-1 scheme applied in DC/DC converter integrated to a PEM fuel cell system

This research presents and compares the outcomes of experimental implementations of different fuzzy logic control structures for a proton exchange membrane fuel cell (PEMFC). These devices are well known for their capability to transform chemical energy into electrical with low emissions. Commonly, a PEMFC has a linkage with a boost converter which allows a suitable end-user voltage through a nonlinear control law. Hence, the contribution in this sense is the experimental comparison of two fuzzy logic strategies known as type-1 and type-2 that were implemented in a PEMFC system. The approaches were embedded in a control board dSPACE 1102 which also has the capability to acquire data. The contrast of results showed capabilities improvement against disturbances in terms of error reduction, control signal, and robustness.The authors wish to express their gratitude to the Basque Government, through the project EKOHEGAZ (ELKARTEK KK-2021/00092), to the Diputación Foral de Álava (DFA), through the project CONAVANTER, and to the UPV/EHU, through the project GIU20/063, for supporting this work

Fuzzy Logic Approach for Maximum Power Point Tracking Implemented in a Real Time Photovoltaic System

Photovoltaic (PV) panels are devices capable of converting solar energy to electrical without emissions generation, and can last for several years as there are no moving parts involved. The best performance can be achieved through maximum power point tracking (MPPT), which is challenging because it requires a sophisticated design, since the solar energy fluctuates throughout the day. The PV used in this research provided a low output voltage and, therefore, a boost-converter with a non-linear control law was implemented to reach a suitable end-used voltage. The main contribution of this research is a novel MPPT method based on a voltage reference estimator (VRE) combined with a fuzzy logic controller (FLC) in order to obtain the maximum power from the PV panel. This structure was implemented in a dSpace 1104 board for a commercial PV panel, PEIMAR SG340P. The scheme was compared with a conventional perturbation and observation (P&O) and with a sliding mode controller (SMC), where the outcomes demonstrated the superiority of the proposed advanced method.This research was funded by the Basque Government, Diputación Foral de Álava and UPV/EHU, respectively, through the projects EKOHEGAZ (ELKARTEK KK-2021/00092), CONAVANTER and GIU20/063

Pitch Control of Wind Turbine Blades Using Fractional Particle Swarm Optimization

To achieve the maximum power from wind in variable-speed regions of wind turbines (WTs), a suitable control signal should be applied to the pitch angle of the blades. However, the available uncertainty in the modeling of WTs complicates calculations of these signals. To cope with this problem, an optimal controller is suitable, such as particle swarm optimization (PSO). To improve the performance of the controller, fractional order PSO (FPSO) is proposed and implemented. In order to construct this approach for a two-mass WT, we propose a new state feedback, which was first applied to the turbine. The idea behind this state feedback was based on the Taylor series. Then, a linear model with uncertainty was obtained with a new input control signal. Thereafter, the conventional PSO (CPSO) and FPSO were used as optimal controllers for the resulting linear model. Finally, a comparison was performed between CPSO and FPSO and the fuzzy Takagi–Sugeno–Kang (TSK) inference system. The provided comparison demonstrates the advantages of the Taylor series with combination to these controllers. Notably, without the state feedback, CPSO, FPSO, and TSK fuzzy systems cannot stabilize WTs in tracking the desired trajectory

Machine Learning Approach for Modeling and Control of a Commercial Heliocentris FC50 PEM Fuel Cell System

In recent years, machine learning (ML) has received growing attention and it has been used in a wide range of applications. However, the ML application in renewable energies systems such as fuel cells is still limited. In this paper, a prognostic framework based on artificial neural network (ANN) is designed to predict the performance of proton exchange membrane (PEM) fuel cell system, aiming to investigate the effect of temperature and humidity on the stack characteristics and on tracking control improvements. A large part of the experimental database for various operating conditions has been used in the training operation to achieve an accurate model. Extensive tests with various ANN parameters such as number of neurons, number of hidden layers, selection of training dataset, etc., are performed to obtain the best fit in terms of prediction accuracy. The effect of temperature and humidity based on the predicted model are investigated and compared to the ones obtained from real-time experiments. The control design based on the predicted model is performed to keep the stack operating point at an adequate power stage with high-performance tracking. Experimental results have demonstrated the effectiveness of the proposed model for performance improvements of PEM fuel cell system.This research was funded by the Basque Government, Diputación Foral de Álava and UPV/EHU, respectively, through the projects EKOHEGAZ (ELKARTEK KK-2021/00092), CONAVANTER and GIU20/063

A Robust Maximum Power Point Tracking Control Method for a PEM Fuel Cell Power System

Taking into account the limited capability of proton exchange membrane fuel cells (PEMFCs) to produce energy, it is mandatory to provide solutions, in which an efficient power produced by PEMFCs can be attained. The maximum power point tracker (MPPT) plays a considerable role in the performance improvement of the PEMFCs. Conventional MPPT algorithms showed good performances due to their simplicity and easy implementation. However, oscillations around the maximum power point and inefficiency in the case of rapid change in operating conditions are their main drawbacks. To this end, a new MPPT scheme based on a current reference estimator is presented. The main goal of this work is to keep the PEMFCs functioning at an efficient power point. This goal is achieved using the backstepping technique, which drives the DC-DC boost converter inserted between the PEMFC and the load. The stability of the proposed algorithm is demonstrated by means of Lyapunov analysis. To verify the ability of the proposed method, an extensive simulation test is executed in a Matlab-Simulink (TM) environment. Compared with the well-known proportional-integral (PI) controller, results indicate that the proposed backstepping technique offers rapid and adequate converging to the operating power point.The authors are very grateful to the UPV/EHU for its support through the projects PPGA18/04 and to the Basque Government for its support through the project ETORTEK KK-2017/00033. The authors would also like to thank the Tunisian Government for its support through the research unit UR11ES82