In order to get correct results using the Model Predictive Control (MPC), one must find the suitable values of its parameters. Despite a large number of papers in literature on MPC tuning methods, there is no available analytical approach permitting to identify explicitly the robustness area of a process independently of its order. Here we intend to overcome this limit thanks to an analytical one. The interest of our approach is to be applicable to a wide set of linear controllable and observable single-input single-output (SISO) processes. The issues of optimal closed-loop stability and the energy consumed are addressed in this paper. The proposed method is tested experimentally via a DC motor. Finally, a performance comparison is made with existing methods to emphasize its effectiveness.

In this paper a combination of isolated DC-DC resonant converters is proposed to interface an electrical hybrid system composed of a battery bank as the main energy source and a bank of supercapacitors (SC) as the auxiliary power source. The battery bank is connected to a DC-bus via an isolated LLC resonant converter, while the SC bank is coupled to the DC-bus through a symmetrical bidirectional CLLC resonant converter. This allows soft switching and enables high switching frequency operations, and then guarantee high power density and high efficiency. An energy management strategy for the proposed structure is studied and implemented. The proposed approach relies on the energetic behavior of the sources to share the required power. The simulation results prove the efficiency of the proposed energy management strategy as well as the performance of the resonant converters.

In this paper, the control and energy management strategy are proposed for an electric vehicle (EV) application. The hybrid source is composed of Fuel Cell (FC) and Ultracapacitors (UCs). The proposed energy management is used to share the EV energy requirement between the hybrid energy source, where the UCs are connected to DC-bus through a bidirectional DC/DC converter, and the FC is linked to the DC-bus through unidirectional DC/DC converter. The main purpose of this paper is focused on EV requested power sharing in real time operations between the FC stack and the UCs according to the electrical characteristics of these sources using polynomial correctors. In this study, only the traction operation mode is considered. The validity of the control is proofed through reduced scale experimental tests.

Dead-time is added into traditional pulse width modulation (PWM) control to avoid short circuit of DC link of inverters. The dead-time can cause problems such as voltage loss, increasing the value of total harmonic distortion of the current waveform (THDI) as well as output current distortion at the zero-crossing. To solve these problems, many studies have been made to deal with the dead-time issues. This paper presents a novel dead-time effect elimination method for H-bridge inverters based on three-level PWM strategy. In this paper, a new current polarity detection circuit has been used to remove dead-time between signals. This detection circuit is based on the conduction states of two low antiparallel diodes in IGBT modules. Here, only one power supply is needed for the diode states conduction detection. In this paper, the principle of the proposed method is detailed. Moreover, simulation and experimental results are presented to demonstrate the validity of the proposed method.

This paper presents the supercapacitor parameters variations due to state of charge (SOC), the number of cycles (NbCy), the frequency of DC-current combined to temperature. The goal of this study consists to show the parameters evolution which can serve to determine the lifetime of supercapacitor for different conditions of use. The contribution of the paper is focused on the impacts of charge/discharge current's frequency and the temperature coupled to number of cycles on supercapacitor resistance and capacitance. The proposed method uses several DC-current profiles based on fluctuations and no fluctuations consideration. To do the supercapacitors characterization, the experimental tests based on charge and discharge operations with fluctuating DC-current are done. The experimental tests results are presented and the impacts of state of charge, the number of cycles, the frequency of DC-current and the temperature are analyzed.

Doubly-Fed Induction Generators (DFIG) are widely used nowadays in grid-connected Wind Turbine Systems (WTS). The typical control strategy for WTS is the maximum power coefficient tracking method. However, this method limits desirable ancillary services from WTS, such as power quality improvement in the network. Therefore this paper derives the optimal reference power coefficient of the WTS that can enhance the participation of the DFIG in the load balancing and reactive power support to the grid. The unbalanced power compensation is performed only by the Grid Side Converter (GSC), while a proper reactive power share between the GSC and the rotor side converter is used to achieve optimal active power injection. The performance of the proposed optimization approach, based on the capability curve of the DFIG-GSC in steady state, is compared with the typical maximum power point tracking method. The results were obtained by simulating a 2-MW DFIG-WTS in MATLAB/Simulink.

Common-mode voltage (Vcm) generated by voltage inverters is observed on motor windings. This voltage may induce bearing currents, which can eventually damage AC motors and cause larger common-mode currents. Many methods are proposed to eliminate or reduce the common-mode voltage. Most of these methods reduce the DC-bus voltage utilization and increase the output voltage harmonics. This paper introduces a new Active Common-Mode Elimination (ACME) modulation for three-Level Neutral Point Clamped (3L-NPC) inverters. This method is based on a Modified Space Vector Modulation (MSVM) method and a power circuit system located between the inverter and the induction motor. MSVM eliminates the redundant switching states that produce high Vcm levels. Then, the power circuit system eliminates entirely the Vcm. Simulation results show the effectiveness of the proposed method. This method can increase the utilization rate of the DC bus voltage and to reduce voltage harmonics.

In this paper, an intelligent control strategy based on combination of the "flatness based control technique" and the "perturbation and observation (P&O) MPPT algorithm" is developed and investigated to control a hybrid electric energy source (HEPS). This EHPS is composed of a fuel cell system (FC) and a solar panel (SP), as the main source and a supercapacitor bank (SC), as the auxiliary sources. The main property of this strategy is that the system power flow is managed in different operating modes with the same control algorithm (without algorithm commutation). The power flows between the fuel cell, the SC is controlled by the flatness based control technique while a P&O MPPT technique is developed to control power of the SP. To validate performance of the proposed control of the HEPS, the simulation results are presented.

The purpose of this paper is to present a real time wind simulator and it's different uses. Given the fact that the simulator is based on a doubly fed induction generator, one of the uses can be the study of different aspects of grid connection and impacts of different faults that may occur in normal operation of wind systems. The studied system is a variable speed wind turbine system with a Doubly Fed Induction Generator (DFIG). The stator of the generator is directly connected to the grid while the rotor is connected through a back-to-back converter which is dimensioned to stand only for a fraction of the generator rated power. The simulator is developed using Hardware-in the-Loop techniques and in order to provide the static and dynamic characteristics of a wind turbine system. We analyzed and developed an experimental system consisting of two main parts: a real time software simulator and an electromechanical system. The Electromechanical System is composed from three electrical drives: an asynchronous machine that emulates the wind turbine, an asynchronous generator, used to study the energy conversion and grid connection problems. The Software simulator is a supervising and control subsystem and is composed from a computational unit and different interface devices. This subsystem is designed equally to study the capability of the classical network to support wind turbine penetration and grid faults impacts. Experimental results from the simulator are presented in order to compare different simulation procedures.

This paper presents the ultracapacitors and the fuel cell (FC) connection for hybrid electric vehicles (HEVs) applications. An original method for the embedded energy management is proposed. This method is used to share the energetic request of the HEV between the ultracapacitors and the FC. The ultracapacitors are linked to dc-bus through the buck-boost converter, and the FC is connected to dc-bus via a boost converter. An asynchronous machine is used like traction motor or generator, and it is connected to dc-bus through an inverter. A dc-motor is used to drive the asynchronous machine during the decelerations and the braking operations. The main contribution of this paper is focused on the embedded energy management based on the new European drive cycle (NEDC), using polynomial control technique. The performances of the proposed control method are evaluated through some simulations and the experimental tests dedicated to HEVs applications.

In this paper, we display experimental results about the measurement of repeatability of an industrial Kuka robot. We first study the distributions of the angular positions and show that these distributions can be considered as Gaussian. We compute repeatability in different locations of the workspace using the experimental angular covariance matrix and the stochastic ellipsoid modeling. We measure repeatability and observe a high variability. We explain the phenomenon by drawing the distribution of the 30 sample repeatability index. We then compare the computed andmeasured repeatability and conclude that our modeling gives good results. We analyse the incidence of weight and workspace location on repeatability and bring additional results to the existing literature.

Most industrial manipulator robots are used in assembly tasks. Their manufacturers use repeatability parameters to show their effectiveness. IS09283 standard details the process of measuring repeatability. As loads, speed and other various factors affect repeatability, a high number of experimental trials are needed to obtain significant values. Moreover, repeatability is also affected by the location of the robot's endpoint in its workspace. In this paper, we construct a stochastic model to evaluate repeatability in the whole workspace of the robot. For this, we only need to determine the robot geometry and sensor sensitivity. Consequently, it is possible with only a few experimental measures to map robot repeatability and obtain relevant information about the spatial error distribution around the points' mean position. This method has been applied to a SCARA robot and has led to specific mapping. Experimental results have been compared with the results of the stochastic ellipsoid model.