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Single-phase phase-locked loop PLLs based on SOGI-QSGs present the most common alternative to the conventional QSG-PLLs and that is on account of their simplicity and efficiency in the extraction of the grid information (phase-angle, voltage amplitude, and frequency) which essential in the control of the power converters connected to the utility grid. In this paper, detail analysis among a set of QSG-PLLs based on SOGI (SOGI-PLL, MSOGI-PLL, MFFSOGI-PLL, SSOGI-PLL, SOGI-PLL-WPF) is presented. The robustness and the performance of the compared PLLs are evaluated using the experimental results under phase-jump, frequency variation, voltage sag, the existence of dc offset, and distorted voltage.

The work presented in this paper concerns modeling, and simulation of a controlled solar pumping system, composed of: photovoltaic panels, power converters, induction motor and the water pump. MPPT FUZZY-LOGIC approach gives better performance optimization of photovoltaic production system according to the sunshine in order to work permanently at the optimum operating point. The pump system is driven by an induction motor. For that, integral backstepping control structure is proposed. It gives interesting features in terms of stability using recursive Lyapunov design, increases robustness despite parameters variation, and provides a good tracking performance. Simulation of the proposed solution is validated under Matlab/Simulink. Results demonstrate clearly that the proposed control structure provides fast dynamic response and stable static power output, even when weather conditions (irradiation) are rapidly changing.

This paper presents a stand-alone photovoltaic (PV) system, which contains a predictive PV emulator (P-PVE), a boosting stage used for Maximum Power Point Tracking (MPPT) and integrated energy storage system, using the cascaded predictive direct power control (CPPC). Generally, in such PV applications with batteries, the used DC/DC converters are separately controlled using several controllers, for that, the proposed CPPC assembles the control of the used converters in the same controller and minimizes only one cost function for all the system by giving more flexibility for the predictive system modelling. The MPPT of the PV emulator and the power management between PV power, batteries power and demanded power are directly included in the proposed control. Simulation and experimental results are carried out to well illustrate and confirm the correctness and the effectiveness of the proposed control.

Generally, the topology of a grid connected photovoltaic system (PV-GCS) includes two or more power converters placed in cascade and they are separately controlled requiring several controllers. In this paper, an optimal cascaded predictive power control strategy (CPPC) for PV-GCS is presented. The method considers the three cascaded power converters (Buck converter, Boost converter and a three phase Voltage Source Inverter VSI) as one stage system and controls them at the same time with the same optimized cost function, providing more flexibility and simple controllability and allows the system able to compensate the undesired grid reactive power. Also, the functioning at the maximum power point (MPP) is ensured by the same control method. The presented research is validated by detailed simulation and experimental tests, which confirm the suitability of the proposed method for PV-GCSs.

This work presents a study about the control strategies applied on the wind turbine in different operation modes. The produced wind turbine power is optimized in a wide range wind speed thanks to the applied controls in all the operation regions. The strategy of (MPPT) is applied when the wind power is lower than its nominal value. However, in high power relatively the rotation speed and the produced power are limited to their nominal values. The simulation results proved the validity of the mathematical model and the control strategies applied in all operation regions. They show that the proposed controls ensure the continuity of the electric energy production in high wind speed relatively with a good protection of the WECS.

This paper studies the modeling and the controls applied on a real wind turbine (V52) in different operation modes. According to the available wind power and the nominal power, the wind turbine produced power is optimized in a wide range wind speed thanks to the applied controls in all operation regions. When the power is lower than its nominal value, the maximum power point tracking (MPPT) strategies is applied. However, in high rotation speed and high power relatively, the rotation speed and the produced power are limited to their nominal values, all these is ensured by an intelligent neural network controller. The simulation results proved the validity of the model and the control strategies applied. They show that the proposed controls are efficient solutions to protect the Wind Energy Conversion System (WECS) and ensure the electric energy production in high wind speed relatively.

This paper addresses the problem of optimal control and scheduling of Networked Control Systems over limited bandwidth deterministic networks using some insight on the interplay between the control and information theory. The motivation is related to the necessity of choice a communication sequence which maximize control signal impact on the plant behavior. The solution is obtained by decomposing the overall problem in a twofold one. The first level problem aims obtaining the periodic off-line or static scheduling function of control signals based on system properties, communication constrains, periodicity of scheduling sequence, performance criteria and maximization of the degree of reachability/observability of the periodic system. A Mixed Integer Quadratic Programming (MIQP) problem is formulated and solved obtaining a periodic and stable NCS. The solution of the second level problem is based on the structure of the static scheduling function obtained from the first level solution and the dependance of the degree of reachability/observability on the current state of the system.

This paper studies the real wind turbine installed in Kaberten (Adrar), in south western Algeria. It is based on Doubly Fed Induction Generator (DFIG) connected to the grid. The main objectives of this research is to create a good model which reflects the real behavior of the studied Wind Energy conversion System (WECS), the optimization of the captured wind power, and the improvement of its performance. In this context, various control strategies were applied. When the power is lower than its nominal value, two Maximum Power Point Tracking (MPPT) strategies were applied and compared. When the power is over or closer to the nominal value, the speed limit and pitch angle controls based on Artificial Neural Network (ANN) approach are applied. The simulation results were compared to the real data of the Supervisory Control and Data Acquisition (SCADA). They proved the validity of the model and the performance improvement.

A novel version of nonlinear induction motors (IM) control algorithm based on the backstepping approach has been proposed in this work. For that, the conventional mathematical model of IM is replaced by the multiscalar one, which is more suitable for application of the backstepping design. By using such combination, the system has fast dynamic response, better load disturbance rejection capability, less parameters sensitivity and better tracking performance of rotor speed and rotor flux magnitude. The effectiveness of the proposed control structure is validated by simulation as well by experiment under critical disturbance conditions.

This paper presents a sensorless direct active and reactive power control (DPC) of grid connected DFIG using back to back PWM voltage source converters in the rotor circuit, the sensorless DPC has been proposed to overcome the drawbacks of large power ripple and variable switching frequency in classical LUT DPC. In this approach two vectors are applied during one control cycle and their periods are obtained in a very simple way. The stator active and reactive powers are made to track references using hysteresis controllers without including any synchronous coordinate transformations. A switching table is used to directly determine the first active vector, and to improve the system robustness with constant switching frequency a second null vector is also chosen, exhibits lower power ripples and better harmonic performance of stator and rotor currents. A sensorless method is implemented for detection of the rotor position based on the comparison between actual and estimated rotor currents. It has some similarity to the model reference adaptive system (MRAS) approach, but a hysteresis comparator is used instead of a proportional integral (PI) controller. Simulation results on a 2 MW DFIG system are provided to demonstrate the effectiveness and robustness of the proposed control strategy.

For a vehicle hybrid electric (VHE) system powered by the batteries and supercapacitors (SC), a real-time optimal power management (OPM) algorithm is proposed based on the look-ahead route information in consideration of the complex traffic environment. At first, a configuration and modeling of the VHE system is addressed. Then, enlighten by the model predictive control (MPC), multiple route information including the traffic and the road terrain over a look-ahead horizon is utilized to predict the future states, and a cost function to minimize total energy loss of the VHE system is given. On above preliminaries, the dynamic programming (DP) algorithm is applied recursively over the look-ahead horizon to update the optimal power distribution between the battery and SC during the total route. Finally, the simulation results confirm that the computational time of OPM has been reduced significantly although a part of energy efficiency is sacrificed. Moreover, the behavior of OPM is similar to that of a skilful driver and thus appropriate be applied to the practical traffic environment.

The stability of neutral systems with mixed delays is studied in this paper. A new discretized Lyapunov functional method is proposed. The method in this paper is less conservative than the existing ones and the results are very close to the analytical results. In addition, this method allows the coefficient matrix of the neutral term to have time-varying uncertainties.

This paper proposes a sensorless direct power regulation based sliding mode control of a wind energy system. The aim of this paper is to evaluate the performance of the system control and tracking accuracy of rotor position estimator. Sliding mode approach introduces a direct calculation of rotor side and grid side converter voltages by the control law developed. A model-reference adaptive system (MRAS) is used to estimate the rotor position. Simulation results for the system are provided to demonstrate the effectiveness and robustness of the used control.

The paper presents a predictive direct power control of a Doubly Fed Induction Generator (DFIG) via a Direct Matrix Converter (DMC) for use in variable speed Wind Energy Conversion System (WECS). The proposed control method combines the merits of Finite States Model Predictive Control (FSMPC) in term of flexibility to the ones of DFIG control in term of maximum power extraction over a large range of wind speeds. The proposed control algorithm selects the switching state of the Direct Matrix Converter (DMC) that minimizes the error between rotor currents predictions to their computed values for all different voltage vectors. The optimal voltage vector that minimizes a cost function is then applied to the DFIG rotor terminal. Moreover, the proposed predictive control is easily extended to minimize the stator and rotor reactive power with unity power factor operation. Simulation results show that the proposed control method is intuitive since it is simple, multi-objective, avoids inner loops and provides best dynamic performance.

In a wide category of embedded systems, sensors, controllers and actuators are located in distant locations. To ensure the control functions, these components need to be interconnected. Usually, communication networks are chosen to support the required communication exchange. In the context of the automotive industry, the Controller Area Network (CAN) bus is yidely used because of its interesting properties. In theory, a CAN network can ensure real-time communications, when no transmission errors are detected. However, an incrpasing numher of applications are sharing this hus, generating jitter and delays on the exchanged messages, which can degrade the performance of control applications. In this paper, the distributed implementation of an active suspension controller is modelled in Simulink thanks to the use of the tool box TRUETIME. The network traffic is generated using the well-known SAE benchmark. Using this simulation model, the control performance of the active suspension system is studied as a function of the available network bandwidth

Since Permanent Magnet Synchronous Motors (PMSM) came in use in industry, major research (Furuhashi, 1992), (Chen et al., 2000), 436 (Misawa, 1987), (Fakham et al., 2004), (Fakham et al., 2005) was done to eliminate sensors that are needed for proper control. Tllis leads the whole system (motor and control) to be cheaper and more robust to noises and other “electrical pollution”. Tltis paper proposes the observability analysis of PMSM as a high order nOlllillear system. Also it presents a design of a sliding mode observer based 011 back EMF which has a good robustness against the variation of electrical parameters of the motor. The effect of the variations of motor parameters such as stator resistance and stator inductance has been studied too. The simulation and experimental results are shown to demonstrate the effectiveness of the approach.

The rapid development of Mobile Internet and Smart Devices and advent of a new generation of Intelligent Transportation Systems (ITS) increase information about present driving conditions and make its prediction possible. Real time traffic information systems (TIS) like SYTADIN help in route to destination planning and traffic state prediction. Energy-optimal routing for electric vehicles creates novel algorithmic challenges where the computation complexity and the quality of information on traffic state are the main issues. This complexity is induced by the possible negative values of edge energy as well as the variability of route and vehicle variables which render the standard algorithms unsuitable. In this paper the authors present an Energy Optimal Real Time Navigation System (EORTNS), implemented on Samsung Galaxy Tab, capable of calculating the route to destination based on information flow obtained from SYTADIN. As an application example the authors propose a real time energy management for a Hybrid Electrical Vehicle (HEV) composed of batteries and Super-Capacitors (SC). The EORTNS is not only capable of energy optimal route to destination calculation with respect to traffic state but also operates the On-Board power splitting between batteries and Super-Capacitors.

This paper presents a Direct Power Control (DPC) for the Rotor Side Converter (RSC) of Doubly-Fed Induction Generator (DFIG) connected to the wind energy conversion system, as an alternative to the classical vector control (FOC). In this work a simple but effective DPC is proposed to achieve quick response and acceptable steady state performance at reason of using a conventional switching table to select the appropriate voltage vectors to the Rotor Side Converter (RSC). Furthermore for controlling Grid-Side Converter (GSC) system a conventional Direct Power Control (DPC) strategy will be compared with Fuzzy Direct Power Control (F-DPC) for controlling Active and reactive power flow exchanged with grid. Simulation results on a 2 MW DFIG system using MAT-LAB/Simulink are provided to demonstrate the effectiveness and robustness of the proposed control strategy during variations of active and reactive power, rotor speed, and converter dc link voltage.

This paper deals with rotor resistance estimation for induction motors drives purpose. A novel MRAS structure for rotor resistance adaptation is proposed. It is based mainly on the use of a very robust sliding mode flux observer as reference model, which gives robustness to the whole parameter estimation operation. Unlike to classical MRAS structure, based on the use of pure integrators, which have initial value and drift problems. By using the proposed MRAS-Sliding mode observer, system has a better performance and robustness. Effectiveness of this proposed estimation structure is verified by experiment under critical disturbance conditions.

The rapid development of mobile Internet and smart devices and advent of new generation of Intelligent Transportation Systems (ITS) increase information about future driving conditions and makes on-board energy management of Hybrid Electrical Vehicle (HEV) realistic. In this paper we propose a real time energy management algorithm RTEMA for a HEV composed of batteries and Super-Capacitors (SC). We suppose that the On-board Dedicated Computer (ODC) has a permanent Internet connection and has the possibility to perform Google-Maps application queries to calculate 3D route to destination. Based on 3D route to destination and average speeds for each road segment the state of charge (SOC) for battery and SC at the end of each receding horizon are predicted. A cost function considering the efficiency of battery, SC, DC/DC converter and electric motor as well as the battery life cycles increase is presented and an optimization problem is formulated and resolved. As ODC for real-time communication and computation we use Samsung Galaxy Pad which is an Android smart device. Performance results in terms of energy optimization, increased battery life and computing time are given which show the practical usefulness of this approach and application. Such a system can be made available to potential users of HEV as well as to the Android community driver members who share information on the state of traffic flow via their Android mobile phones [30].

A novel structure of nonlinear integral backstepping control has been proposed for induction motors. We can see clearly that the structure of the controller generated by the classical version of backstepping is composed of a proportional action, which was added a derivative action on errors. Such a structure makes the system sensitive to measurement noise. The lack of integration means also the appearance of a constant static error, caused mainly by non-zero mean disturbances. The solution to this problem is to design a new version of the backstepping with integral action. By using the proposed integral backstepping controller, the system has a better load disturbance rejection capability. The effectiveness of this proposed control structure is verified by simulation as well as by experiment under critical disturbance conditions.

The performance of networked control systems based on a switched control law is studied. The control law is switched between sampled-data feedback and zero control, the switch instant of which is determined by a switching parameter. The objective of this paper is to analyze 1) under what condition the switched control law can lead to better performance than the standard one and 2) how to select the switching parameter if the condition is satisfied. Numerical examples show the effectiveness of the proposed results.

International audience; Congestion control is a fundamental building block in packet switching networks such as the Internet due to the sharing of communication resources. It has been shown that the plant dynamics is essentially made of an integrator plus time delay and that a proportional controller plus a Smith predictor is a simple and effective controller. It has been also shown that the today running TCP congestion control can be modelled using a Smith predictor plus a proportional controller. Due to the importance of this control structure in the field of data network congestion control, we analyze the robust stability of the closed loop system in the face of delay uncertainties that in data networks are present due to queuing. In particular, by applying a geometric approach, we derive a bound on the proportional controller gain which is necessary and sufficient to guarantee stability given a bound on the delay uncertainty.

A novel structure of backstepping control has been proposed for indirect field oriented control of induction motor drive. Voltage and current signals are usually contaminated with high frequency switching noises due to SVPWM inverter. The proposed structure avoids real time integration and its associated drift problems, which in practice are the source of generation of unwanted noise. These problems are typical in the PI controllers used in conventional indirect vector control for speed and current regulation. By using the proposed backstepping controller, the system has a good load disturbance rejection capability, fast dynamic response and less parameters sensitivity. The effectiveness of this proposed control structure is verified by simulation as well as by experiment under critical operating conditions.

A Fast Dynamic Programming (FDP) algorithm is proposed to optimize the fuel consumption of the Plug-in Hybrid Electronic Vehicles (PHEV) over a prescribed driving cycle. Firstly, an innovative DP mathematical model for PHEV with reduced dimension is created. It composes of a linear state transfer equation and a quadratic cost function with 1×1 dimension. Based on this model, two algorithms expressed as the simple analytic forms are derived. One is the control algorithm for the optimal power splitting ratio (PSR) between the internal combustion engine (ICE) power and demand power. Another is the recursive algorithm to calculate the optimization value of the fuel consumption. Then, the optimal output power of ICE (or electronic motor (EM)) and the optimal speed ratio of the gear position can be calculated rapidly as the consequence of using the algorithms with analytic forms. Finally, the simulation results confirm that the computational efficiency of the FDP control algorithm has been improved with a geometric ratio, while its control performance maintains in an acceptable range in contrast with conventional DP control algorithm.Copyright © 2009 by ASME

International audience; A switched model-based control for networked control systems is studied in this paper. The control law is switched between model-based control and zero control, the switch instant of which is determined by a switching parameter. The objective of the paper is to analyze under what condition the switched control law can lead to better performance than the standard model-based control and how to select the switching parameter. Numerical examples show the effectiveness of the proposed results.

This article addresses three stability problems related to networked-control systems (NCSs) with periodic scheduling, where control systems may have multiple samplings in a hyperperiod (a hyperperiod is a periodically repeated scheduling sequence for all tasks in an NCS). As expected, the analysis of a system with multiple samplings is much richer than the case with single sampling. For example, a system with two samplings may be stable (unstable) even if it is unstable (stable) when sampled by either sampling. In this context, it is important to understand how network-induced delays and multiple samplings affect the system's stability. In this article, three particular stability problems involving constant and/or time-varying parameters are investigated, and the corresponding stability regions are derived. Numerical examples and various discussions complete the presentation.