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International audience; The lack of precise mathematical model of nonlinear systems, such as electric machines, brings certain limits to design a powerful controller for such systems. This article presents a model-free-adaptive-control (MFAC) scheme as a good alternative to the commonly used model-based-control (MBC) methods in order to improve the controller design limitations due to the need for system model information. In this regard, an MFAC is developed in this article for current control of a wound rotor synchronous machine (WRSM) drive system and compared with a proportional-integral (PI) controller as a well-known model-based controller. Since the controller performance can be affected by unexpected phenomena, such as model errors, parameter variations, and changes in operating point, beforehand, the robustness of developed MFAC is first tested under the mentioned conditions in the simulation area. Then, through experimental validation on a specifically designed test bench, a satisfactory performance was obtained for the MFAC scheme.

International audience; Sensorless control theory is considered as one of the most important keys to reduce the cost of manufacturing and maintenance in automotive applications. This article presents a current sensorless control algorithm of a wound rotor synchronous machine using a model-free-adaptive control (MFAC). The only controlled variable in this method is the rotor speed, and no observation or estimation will be performed on the phase currents. The presented controller is also compared with a current sensorless control method that uses a Lyapunov-based observation of phase currents in the control algorithm. The developed control algorithm is first tested in simulation under several operating conditions, such as starting, tracking, parameter variation, and load step. Then, experimental tests validated the effective performance of MFAC in a current sensorless control algorithm. According to these results, the control of phase currents is guaranteed with a small error but without using any current sensors.

International audience; It is well known that the interaction between cascaded individually designed power conversion systems can cause instability. To overcome this issue, a Hamiltonian energy control scheme is proposed, which is based on passivity control theory and port-controlled Hamiltonian framework. A complementary PI adjustment term is also included in the control algorithm to eliminate the steady-state output voltage error caused by the parameter uncertainty. The proposed control approach is applied to three different cascade structures. First, the cascade structure between dc/dc converters is considered, and the detailed controller design is given. Second, the cascade connection of a single converter and its LC filter is studied. By placing the LC filter into the Hamiltonian model of the controlled converter system, the dynamic and potential instability caused by the filter can be adjusted. Finally, the cascade structure between subsystems including filters and converters, which are common in microgrids, is studied. By using the Hamiltonian function (storage function) as the Lyapunov function candidate, the large-signal stability of each controlled converter system is proved. When the cascade structure contains multiple controlled converter systems, the stability of the entire cascaded system is guaranteed by the superposition of multiple Lyapunov functions. A 3.5 kW 220-270-350 V test bench is built in the laboratory to demonstrate the application of the proposed control approach to these three cascade structures.

International audience; Series connection of input filters with static converters might lead to instability. However, the input filter has rarely taken into account in the stable design of power converters. Indeed, an input LC filter cascaded with a converter can become unstable, and so even if the converter is regulated by a tight controller ensuring its stability alone. This fact is due to the interactions between the filter and the converter. To tackle the instability potential, an Adaptive Energy Shaping Control (AESC), which is based on the Interconnection and Damping Assignment Passivity-Based Control (IDA-PBC), is addressed in this paper to regulate the cascaded system and achieve the following attractive features: 1) The input filter’s dynamics are considered in the control law, so the interactions between the filter and the converter are taken into account during the controller design; 2) The influence between several subsystems, put in cascade, is considered by the proposed method and the new large-signal stability proof is given accordingly. Simulation and experimental results from a 3.5 kW 270 V–200 V buck converter cascaded with an input filter under different load conditions, i.e. Constant Impedance Load (CIL), Constant Current Load (CCL), and Constant Power Load (CPL), are presented to demonstrate the proposed approach.

International audience; In this paper an online identification method based on a model of a Wound Rotor Synchronous Machine (WRSM) is proposed. With this method, all the values of the electrical and electromagnetic parameters are determined with no need for any prior knowledge of the machine parameters. In this method, two new parameters are proposed which represent the whole parameter error. An Extended Kalman Filter (EKF) is used to estimate these two new parameters. So that, by operating the machine at three distinct operating points, all the parameter errors can be calculated. To validate the proposed method, in addition to simulation, an experimental test is also performed on a WRSM.

International audience; In control of electric machines, removing the current sensors from the electric powertrains has a great importance owing to saving on manufacturing and maintenance costs. This paper addresses the Model-Free-Controller (MFC) as a current sensor-less controller that do the control task for a Permanent-Magnet-Synchronism-Machine (PMSM) without using neither sensor nor estimator for stator current. As this controller is model free, it doesn't require any information about parameters. MFC tries to control the drive system just with measuring the rotor speed and dc bus voltage. Simulation study has been done to show the MFC's robustness under ideal and parametric error condition.