is an open access repository that collects the work of Arts et Métiers ParisTech researchers and makes it freely available over the web where possible. Abstract -This paper proposes a new method based on Artificial Neural Networks for reducing the torque ripple in a non-sinusoidal Synchronous Reluctance Motor. The Lagrange optimization method is used to solve the problem of calculating optimal currents in the d-q frame. A neural control scheme is then proposed as an adaptive solution to derive the optimal stator currents giving a constant electromagnetic torque and minimizing the ohmic losses.Thanks to the online learning capacity of neural networks, the optimal currents can be obtained online in real time. With this neural control, each machine's parameters estimation errors and current controller errors can be compensated. Simulation and experimental results are presented which confirm the validity of the proposed method.
The interlinking converters is one of the important components in the hybrid mirogrid system, the study of structure and control method of the interlinking converters in hybrid mirogrid has been implemented and achieved positive results. This paper proposes an improved decentralized control of level-shifted carrier-based PWM for a modular multilevel interlinking converter (IC-MMC) in standalone hybrid microgrid (HMG-Hybrid Microgrid). Main research objectives is to study the capability of the decentralized control method proposed for the IC-MMC unit when performing the power exchange control task between the DC and AC bus in the HMG system, increased flexibility in controls. Furthermore, the proposed control method for IC-MMC for HMG is also verified in term of dynamically reconfiguration when changing the number of modules in the MMC when the improve of system reliability is needed. The feasibility of the carrier level shift control method for IC-MMC in HMG has been verified by simulation model on MATLAB/Simulink software to evaluate the ability to exchange power between the DC bus and the AC bus.
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