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Rapid and low-cost 3D scanning system becomes a common solution for prosthetic designers and engineers to acquire accurate 3D geometrical model of the involved patient. Multiple Kinect sensor fusion solutions have been proposed but still, there is a lack of fusion scheme within a single workstation and a systematic reconstruction error analysis. The objective of the present study was to develop a new Kinect sensor fusion scheme running on a single workstation and an error compensation strategy. Architecture of a 3D scanning system for the lower residual limb was proposed. Four Kinect sensors were used to develop the fusion scheme. An error compensation approach based on linear regression method was performed. Then, an iterative rigid multi-set registration method was proposed. Different primitive geometries (cylindrical objects, box) with well-known physical dimensions were designed, fabricated and used for the evaluation process. Obtained results showed that the error compensation strategy leads to a reduction of around 40% of 3D geometrical reconstruction error for the residual stump-like structure. The total scanning and processing time is 25.4 ± 2.5 seconds. Moreover, our novel iterative rigid multi-set registration method leads to an improvement of accuracy of 60% compared to conventional registration method. Our proposed 3D scanning system using multiple Kinect cameras with error compensation strategy is expected to reduce the design cost and improve the design accuracy. As perspective, this 3D scanning system with fusion scheme will be integrated into a Computer-Aided Design (CAD) system with soft tissue deformation feedbacks for lower limb prostheses.

Multiple types of Demand Response Programs (DRPs) are offered within the same infrastructure. Multiple objectives of technical, economic and marketing order are targeted. Defining a model with weights for the various objectives and the related Key Performance Indicators (KPIs) is of a high importance. A structured model can be achieved through the assessment of an adequate market design with adequate dynamic pricing schemes to be offered to consumers, coupled with reducing costs at various levels and optimizing the technical indices while using business intelligence and big data. The originality of this paper resides in the simulation of a model combining multiple DRPs with multiple objectives and their assigned weights, hence the elasticity of dynamic parameters and criteria selection to achieve the compromise. It includes the proposal of dynamic pricing schemes for consumers’ detected clusters while optimizing costs and considering technical constraints. The optimal solution is the result of combining an assessment process based on historical data coupled with intensive what if scenarios to serve the planning and optimization phase, thus its application will be guaranteed. The validation is preformed through a simulation on Matlab using multi-objective optimization clustering based with assigned weights.

Energy produced by wind turbines is characterized by its uncertainty which causes high fluctuations. Two types of fluctuations exist: the first one is represented by the slow power variation measured during large period; the second is the fast power variation measured from minute to minute that is known by the ramping rate. In this paper, the second type is studied. The high level of penetration of these fluctuations may affect the power network quality and may cause voltage and frequency instability. Power smoothing that is defined in this paper by ramping rate control is an important issue to avoid these fluctuations and to maintain the power network stability. Conventional methods based on storage system and on delta control of wind turbines are published in literature for this purpose. Unfortunately, storage systems are either small or expensive and delta control reduces yield energy. Another approach consists of adding to the delta control the power consumption control of heating and ventilation air conditioning (HVAC) systems installed in large buildings. This would provide positive and negative electrical power reserve for the compensation of wind power fluctuations. Unfortunately, this technique is still limited by a small margin of control since neither the temperature nor the humidity of the air-conditioned zones should be affected. This paper suggests an improvement of this margin of control by integrating in the regulation process the supply fan with the return fan. A numerical study based on real data shows that the proposed method is more advantageous than using slow response heat storage systems or expensive storage batteries or DC controllers. Moreover, this method reduces wind power losses and keeps the temperature variation unperceived, although an important reduction in electrical power fluctuation is achieved.

Integration of the renewable energy sources (RES) in distribution systems is accompanied with a lot of challenges to power system protection, control and operation. This integration can cause reverse power flow that affects the voltage stability of the power system. To avoid the power system instability, the monitoring of the integration of RES is necessary. In this paper a hybrid algorithm is proposed to monitor reverse power flow, and then it was tested on the IEEE-39 and IEEE-118 node test feeders.

Multiphase induction generators are gaining popularity in wind energy systems for their robustness, reliability and fault-tolerant behavior when compared to the famous three-phase ones. This work proposes an advanced robust nonlinear control strategy for a multiphase induction generator in a variable speed wind energy conversion system. The considered structure in this paper consists of a six-phase induction generator and two conventional three-phase two-level voltage source converters. The stator currents of the structure are regulated using the proposed method that consists of a time delay estimation-based modified super-twisting. On one hand, and a proportional-integral regulates the speed in an outer control loop. On the other hand, the proposed method regulates the stator currents in an inner control loop. The stability analysis of the closed-loop error dynamics is proved using a quadratic Lyapunov function. Finally, numerical simulations have been carried out on a model of a real six-phase induction generator to show the good features of the designed method.

Our study consists of analyzing and comparing the Linear Fresnel system and the Parabolic Dish-Stirling system with the aim of installing a 100 MW concentrated solar power plant in Lebanon, a region in the Middle East with abundant solar radiation. The comparison is done in both technical and economic aspects, in which both systems are evaluated for a possible transition from fossil fuel to solar energy. The variation of the temperature and solar radiation parameters will enable us to measure the performance of each system.

Demand side management (DSM) is a technical program that have the purpose of smoothing the load curve by reducing its peaks and filling its valleys, and of ancillary services and frequency regulation. Many demand response programs (DRP) are used for this purpose. The thermostatically controlled load (TCL) are the most efficient programs used for DSM and especially for ancillary services. In this work, we study the heating ventilation air conditioning (HVAC) system as one of appliances that fall under the category of TCL. In literature, the chiller power variation due to direct control of HVAC supply fan speed is not considered for DSM. This paper fills this gap and increases the participation capacity of HVAC. Therefore, the HVAC system is remodeled in order to express with more accuracy the chiller power variation. The new model relates the chilled water temperature to the leaving air temperature. Simulation results shows the improvement provided by this method.

High peak demand is one of the major problems induced by the penetration of a high number of Plug-in Electric Vehicles (PEVs) on the distribution system. Although time-varying electricity price, demand response, and incentive programs are suggested in many papers as solutions to smooth the peak-load, the results are not satisfactory. For example, in the presence of a dynamic price, all PEVs at homes tend to charge during periods when the electricity price is low. They may create peak demands that exceed the transformer power limit in unexpected periods when the power consumption is low. The situation gets worse when a fixed price is used in some countries and regions. PEVs tend to charge at any time without considering the presence or not of a peak load. To solve the problem of high penetration level of PEVs, we propose three novel contributions as follows, (i) a novel power Soft-Constraint at home level, (ii) a novel Multilevel Power-based Soft-Constraint, and (iii) a new Multilevel Power-based Electricity Tariff System are proposed. Simulation results show that our approach improves the integration of PEVs even when high penetration level is considered and even when fixed electricity price is used.

Accurate daily river flow forecast is essential in many applications of water resources such as hydropower operation, agricultural planning and flood control. This paper presents a forecasting approach to deal with a newly addressed situation where hydrological data exist for a period longer than that of meteorological data (measurements asymmetry). In fact, one of the potential solutions to resolve measurements asymmetry issue is data re-sampling. It is a matter of either considering only the hydrological data or the balanced part of the hydro-meteorological data set during the forecasting process. However, the main disadvantage is that we may lose potentially relevant information from the left-out data. In this research, the key output is a Two-Phase Constructive Fuzzy inference hybrid model that is implemented over the non re-sampled data. The introduced modeling approach must be capable of exploiting the available data efficiently with higher prediction efficiency relative to Constructive Fuzzy model trained over re-sampled data set. The study was applied to Litani River in the Bekaa Valley – Lebanon by using 4 years of rainfall and 24 years of river flow daily measurements. A Constructive Fuzzy System Model (C-FSM) and a Two-Phase Constructive Fuzzy System Model (TPC-FSM) are trained. Upon validating, the second model has shown a primarily competitive performance and accuracy with the ability to preserve a higher day-to-day variability for 1, 3 and 6 days ahead. In fact, for the longest lead period, the C-FSM and TPC-FSM were able of explaining respectively 84.6% and 86.5% of the actual river flow variation. Overall, the results indicate that TPC-FSM model has provided a better tool to capture extreme flows in the process of streamflow prediction.

Actual research concerning the detection of explosive materials is suggesting different methods and the use of different kind of sensors. The QCM method, for example, has become a subject of interest because of its high sensitivity and accuracy in biomolecules detection in terms of Nanogram. This paper overview the QCM method and presents some measurements and simulation techniques for any possible future improvements (in terms of reliability and accuracy). An explosive vapor detector using QCM method is based on quartz frequency variation principle due to the interaction between deposited enzymes on the quartz surface and explosive vapor in the air. This paper deals with this method's accuracy by means of measurements performed on a specific QCM component and by some simulations performed using COMSOL software.

Nowadays, smart grid for electrical power distribution is considered as one of the most important infrastructures enabling the consumer to interact with other stakeholders to reach technical and economic objectives. This interactivity is performed through the concept of agreements that are signed between different involved actors (utility operators, electrical energy producers, consumers, electrical energy market traders, brokers…). These agreements are of the form of what is called Demand Response Programs (DRPs) which are already greatly diversified. In case of different DRPs implemented over the same network without any coordination, the network stability may get degraded rather than improved. Therefore, in order to make coordination easy to be realized, DRPs implementations based on a generic architecture become a must. In this paper, a novel generic architecture is presented. It is validated first by means of matching existing architectures with the suggested one and second by identifying some of the architecture components while implementing a DRP based on a real case study.

Many studies have concentrated on how to optimize the size and placement of Parking Lots (PLs) on a distribution network. Within this context, this study consists of presenting a systematic approach for sizing the PL in terms of number of simultaneously plugged-in vehicles. This approach is original since it takes into account the loads' profile on the bus where the PL is connected (it is valid for any load profile on the bus), the PL manager benefits and the vehicles' owners requirements. Multiple technical constraints are respected, those imposed by the PL infrastructure and those related to the distribution network. A mathematical model and an algorithm are developed for this purpose using MATLAB.

Short-term hydro generation optimal scheduling of cascade hydropower stations is a typical nonlinear programming problem that minimizes the deviation between the produced power and the grid requirement while satisfying hydraulic and electrical constraints. In this work, the main objective is to find the optimal hourly water discharge rate of each hydro station in a multi-reservoir system to minimize the power deficit. The demanded load is then distributed among the working units of three cascade hydropower stations constructed on Litaini River — Lebanon: Markaba, Awali and Charles Helou. To achieve our goal, methods involving and joining data mining and mathematical programming will serve as a base for a Decision Support Tool (DST). Based on the DST features, a distributed control structure is implemented using a multiple software framework. MATLAB is used for mathematical optimization while LabVIEW is employed to develop Human Machine Interface (HMI) for sequential control.

Due to demand increasing, most of power networks operate close to their stability limits. The high demand and the reduction of non-renewable energy sources impose the insertion of renewable energy sources. Their non-supervised insertion can cause voltage instability. In order to avoid this instability, a coordinated secondary voltage control system (CSVC) should be implemented. This paper describes the proposed procedure of CSVC system implementation. It is composed by three steps. The first step is the power network partitioning based on Self Organizing Map algorithm, the second one is the pilot buses selection based on the reduced Jacobian matrix and on voltage security performance index, and the third one is the CSVC system implementation based on the hybrid control approach using generators and shunt elements. These three steps are described in details in this paper. This procedure is used to maintain the voltage stability of large network. In this paper its efficiency is validated for small network also. Therefore it is implemented on the IEEE 39 bus system.

Based on existing studies to estimate Batteries State of Charge (SOC), many published papers have suggested numeric models to express the relationship between the SOC of a battery in Plug-in Electric Vehicle (PEV) and the vehicle travelled distance. Knowing the battery SOC and based on these relations, other studies concentrated on the prediction of the distance range travelled by a PEV. Reversible linear approaches study the prediction of the SOC knowing the travelled distance or vise-versa. Other more realistic non-linear and not reversible models are published involving more parameters like losses in the battery or not homogeneous trajectories. Based on a wide review of the parameters considered in these models, this paper present a more realistic and accurate one for the SOC prediction. A comparative study with existing models could be easily deduced from this paper in order to show how much the accuracy is improved by considering more parameters.

A new single-phase power factor corrector (PFC) based on the Sheppard-Taylor topology is studied. Compared with conventional PFCs, this topology facilitates a better input current tracking, lower voltage stresses across the devices and larger output voltage range for the same operating area. The converter is integrated as a PFC at the DC-end of a single-phase diode bridge. Pulse-width-modulated (PWM) multi-loops control schemes are proposed and developed in order to ensure a unity power factor at the AC-source side and a regulated voltage at the DC-load side. The first control method uses the simple and robust hysteretic-based controller; the second employs a conventional PI regulator; and the third is based on the model nonlinearity compensation approach. The design of the last two control methods is based on the knowledge of a mathematical model that would accurately represent the converter. This model is developed in this paper using the state-space averaging technique, and then the small-signal transfer functions of the converter are derived for linear control design purpose. The performance of the different control strategies is evaluated through simulation experiments carried out on a numerical version of the converter. The implemented model of the converter is obtained by using the switching function technique. The control system is tested under both rated and disturbed operating conditions. The system performance is evaluated in terms of source current total harmonic distortion (THD), input power factor, DC voltage stabilization, and regulation following load variations.

Plug-in Electrical Vehicles (PEVs) are nowadays increasingly penetrating the car market. Charging stations are becoming a lucrative business especially for the public parking lot owners where they can be installed and operated. PEVs can be used as energy storage elements during low demand and as energy sources during peak demand. Some technical problems related to the management of the charging stations may arise. Simultaneously charging a large number of PEVs in a parking lot may disturb the power system due to an unexpected peak demand. To overcome this situation, some researchers are suggesting different forms of Charging and Discharging Schedules (CDS). A reliable model for the flow of vehicles entering/leaving the parking is very essential to define an accurate CDS. In this paper, a new approach for modeling the flow of vehicles is developed, and it is shown how a CDS is related to it. In addition, it shows how incentive programs can contribute to increasing the financial benefits and at the same time reducing the disturbances on the power network.

The non-supervised insertion of renewable energy sources into electric power networks causes fluctuations that may lead to voltage instability. The simple and coordinated secondary voltage control systems are used to avoid this instability. To obtain maximum regulation performance with optimized number of controllers, an appropriate selection of pilot buses is suggested. In this paper new algorithm is proposed to select optimal pilot buses. This method is based on the singular decomposition of the reduced Jacobian matrix with the voltage security margin index. To evaluate the efficiency of this algorithm, a comparison with the Bifurcation, Clustering with Node-Partitioning Around Medoids and the Hybrid algorithms is proposed. The simulation results show that the proposed algorithm gives optimal pilot buses according to the selection criteria (explained later in the paper).

Recently, sparse matrix converters are gaining the researchers' attention as an improved alternative to traditional matrix converters thanks to the advantages they offer by reducing their number of semi-conductor switches. Three major solutions are found in the scientific literature to increase the voltage transfer ratio limited so far to 0.86; the reverse operation of the matrix converter, the over-modulation of the matrix converter and the introduction of a Z-source network in the dc stage of the converter. In this paper, the Very Sparse Matrix Converter (VSMC) is adopted since it presents the smaller number of switches in the family of bidirectional matrix converters. It is simulated in three configurations designated to increase the voltage transfer ratio while improving the overall performances of the converter in order to facilitate its implementation in the wind conversion systems. First, the VSMC is simulated in normal operation, then in reverse operation. Second, it is simulated with the cascaded Z-source network and finally with the series Z-source network. All four configurations are compared in terms of voltage transfer ratio improvement and output voltages and currents waveforms. Then, further analysis is carried out for the cascaded and series Z-source configurations in order to compare both arrangements. The series Z-source VSMC presents better performances in terms of output current THD and Z-source components reduced constraints.

Solar photovoltaic is currently the technology for electricity production that witnesses the fastest growth in the world. Unfortunately, in the case of an abnormal operating situation, these systems can't be profitable, although technology is improving and prices are decreasing. An abnormal operation is considered in this study when the connectivity to the grid is partial or not possible or when the storage is partially used or not used at all. In this study, technical dimensioning and economic analysis are simultaneously performed in order to find the costless system according to load requirements, storage existing capacity and grid availability. The suggested analytical approach is useful for the case of the most developing countries where the offered subsidies for PV installation are not enough and the operating environment is not ideal. The objective is to find the costless residential system installed in a developing country and the case study of a standard Lebanese house is adopted for validation. The analysis takes into account the solar profile, the average energy consumption, the availability of the grid and the net metering policy.

Penetration of electrical sources based on renewable energies is becoming more and more significant in power transportation and distribution. Changes caused by this integration have an important impact on the network stability. This instability is avoided through the three hierarchical voltage control levels. In this paper we focus on the selection of pilot buses for the secondary level voltage control. Pilot buses are those where regulators are installed and the objective is to find the most appropriate selection that minimizes their number and maximizes the stability performance. A comparison between all existing selection algorithms is performed then an improvement is made on the most performing one. Results are validated by doing simulations on the standard IEEE 118 bus.

This paper presents a review of modulation and control strategies for matrix converters applied to permanent magnet synchronous generator (PMSG) in wind power generation systems. Modulation techniques already discussed in scientific literature for the command of matrix converters are mostly divided into three categories: the scalar modulations, the pulse width modulations and the predictive control modulations. These modulation methods are combined with maximum power point tracking (MPPT)-based control strategies to secure and improve the performance of the overall system. Control strategies are combinations of two elementary blocs: the MPPT algorithms and the regulation approach. MPPT algorithms are crucial for the improvement of wind harvest and regulation approaches are generally based on adaptive, non-linear or linear automatic methods that are responsible for current control or field oriented control or reactive power control.

This paper presents a review of the recent advances in matrix converter topologies used with the permanent magnet synchronous generator (PMSG) in wind power generation systems. Dedicated literatures introduce different topologies inspired by the conventional matrix converter. Two-stage matrix converters known as sparse matrix converters are compared to the conventional matrix converter in terms of implementation complexity, cost, power rating and voltage ratio. Single-phase matrix converters topologies are implemented in high power wind applications in two different modular concepts: the reduced matrix concept for offshore wind farms and the multi-modular high power matrix converter. On the other hand, several modulation techniques applied to the matrix converter-PMSG scheme are briefly presented.

The grid is not all the time available and a daily scheduled program of electricity shortage is applied in some developing countries like Lebanon. In such situation renewable energy systems connected to the grid can't be an effective solution. Although net metering or feed forward connectivity is allowed, still the grid outage program prevents its use in an efficient way. For this reason, this research work suggests a new control algorithm for photovoltaic systems connected to a grid with scheduled outage. This solution provides to the consumer the maximum benefit of connectivity.

This paper presents the design of a MATLAB simulator of a hybrid renewable energy system applied for energy generation in rural regions. The system is simulated using MATLAB. It consists of a set of photovoltaic panels, a DFIG wind farm, a pumped water storage/generation station and it is designated to supply residential/industrial loads. A transmission line connects this system to the main power grid. Although conventional models are used, the work originality consists of performing an optimal control of sources and loads in order to keep power balancing between generation and consumption in both connected and islanded modes.

Landmines are stilled scattered even today in many countries affected by wars. Conventional detection approaches are not optimized because the staff involved in this process although skilled and experimented, requires a long time for a safe and for an efficient detection that uses costly and accurate equipments. Therefore, some research are actually focusing on using wireless sensors networks for this purpose hoping that faster, safer, more accurate and more cost-effective methods will be found. Within this context, this work considers a network made of wireless biosensors randomly spread over the landmines field. It presents a comparative study on the energy consumption when different scenarios of data transfer are adopted. Simulation results are obtained in order to help in finding the optimal solution where the minimum data is lost, the minimum energy is consumed and the minimum redundant data is collected.

Remote Laboratory Experimentation is a technique used in modern engineering laboratories to help academic researchers and students perform laboratory experiments remotely through the internet. Remote control of experiments is gaining more importance in training and education. However, remote real-time training on instruments programming still have some unresolved problems such as error management. In this paper, a platform for training students on remote robotic experiment control through tele-programming is presented. Programming sessions can be done by the trainee at many levels of control with built-in error management in order to avoid system freezing or malfunction. We also present a real experiment: programming navigation control of a mobile robot in the presence of obstacles using fuzzy control.

In order to assure hygiene safety for patients, optimal use of drugs is necessary for controlling the number of clinically observed tumor cells. Based on a mathematical model of drug therapy for cancer, and on an objective function, the optimal solution is reached. The model therapy is considered for an individual patient over a fixed time horizon. The disease dynamics are given by an ordinary differential equation that describes the evolution of cancer cells in time. An optimization theory is applied in order to minimize the number of cancer cells at the end of treatment. A comparative study is performed on different treatments profiles applied to different types of cancer. This study shows the usefulness of the suggested mathematical deterministic or hybrid model. It considers the treatment in terms of duration and drug dosage, the initial number of detected cancer cells and the objective function.

Capacitor banks are used to compensate the reactive power demand of large commercial and industrial loads. When used to switch capacitor banks mechanical breakers generate large current transients. These transients may cause serious system disturbances, premature wear of the breaker contacts and, possibly, shorten the life of the capacitors. While thyristor switches are not new and industry has successfully used them to obtain transient-free switching of capacitor banks, there are very few papers describing this application. This paper tries to fill the void and presents a comparative study of various three-phase configurations of semiconductor switches intended for low voltage (600 V and less) distribution systems. Simple theoretical analysis enables the calculation of the optimal switching times to minimize transients. These calculations take into account the system impedance and the initial capacitor voltages. >

International audience; In this paper, we propose a Hybrid Multi-Channel Multi-hop Medium Access Control (HMM-MAC) meeting the safety and non-safety requirements in Vehicular Ad-hoc Networks when no infrastructure is present (V2V communication) with only a single transceiver at each vehicle. The simulation results showed that our scheme could achieve a higher delivery ratio of road safety messages and a high probability to select a free transmission channel in a certain region and during a certain time

In this paper we propose a new model for tele-rehabilitation based on the Service Oriented Architecture (SOA) approach. SOA can be defined as a group of services that communicate with each other to provide a design framework with a view to realizing rapid and low-cost system development and to improving total system-quality. This approach has proved its efficiency in domains like e-Business and e-Learning. Our approach is so to develop an integrated information system for remote rehabilitations based on a Service Oriented Architecture (SOA).

This paper deals with solving robot cooperative task conflict using robot assistive behavior processing. These conflicts could occur in reactive multi mobile robot task. To manage such conflicts, each robot must assist the other units from their own capacities. A role method based on capacity adjustment is proposed. A role is a specific robot assistive behavior. Conflicts are then compensated by role switching. The same processing can be used in man-robot interaction. In this case, the robot has to define the efficient role in order to assist the man. A specific multi mobile robot conflict problem is studied: a constraint case of a reactive handling task with two mobile robots. This is a critical task since the object transported is only held by robot compression. Any degraded case, hardware failure or tactical conflict occurrences, would lead to a task deadlock. To define the global assistive role, on-line fuzzy reinforcement is used to adjust basic behaviors. In the studied case, no explicit communication is used to define the relationship between the robots in order to be generalized to man-machine cooperation. Our goal is to develop a strategy to manage interaction with handicapped persons. We studied a robotic rollator. In this case, the assistive role of rollator has to be adjusted in order to compensate the man's task.

Remote Laboratory Experimentation (RLE) is a technique used in modern engineering laboratories to help academic researchers and students perform laboratory experiments remotely through the internet. Due to the lack of well specified requirements for RLE, many RLE implementation models exist with different characteristics, using different technologies, and without a consistent set of services. In this work, the services provided by some recent RLE implementations models are identified, these services are analyzed, and specifications of a general improved model are concluded.

In this study, a two-stage DC-DC converter for high current applications is studied. The converter consists of two three-phase full-bridge inverters connected through three AC coupled inductors. A switching-functions-based model of the converter is first established, and then a control scheme is designed for both inverters in order to ensure a high power factor at the AC stage, and a regulated voltage at the DC load. The performance of the proposed control system is verified through numerical simulations. First, an ideal DC source is considered in order to test the performance of the control system, then a proton exchange membrane fuel cell is applied as the DC source in order to highlight the usefulness of this converter in such applications.

This paper presents a comparative evaluation of two multiple-loops duty-cycle-based control schemes applied to a three-phase three-switch three-level boost-type rectifier. The control laws are both elaborated on the basis of a state-space averaged model of the converter, expressed in the synchronous rotating frame. On the one hand, a control scheme that uses linear regulators is designed by using the small-signal transfer functions of the converter’s model, which was linearised on the neighbourhood of a suitable steady-state operating point. On the other hand, a non-linear control scheme that uses the input-output feedback linearisation approach is also designed in order to satisfy the same requirements as for the linear control system. For comparison purpose, both control schemes are implemented numerically using the Simulink tool of Matlab, and simulation experiments are carried out in order to test and verify the tracking and regulation performance of each control law, as well as their robustness towards load or mains source disturbance. For the same operating conditions, the performance of the two control laws are analysed and compared in terms of line currents total harmonic distortion (THD) and DC voltage regulation.