The synergetic control technique (SCT) has the solution for understanding the symmetry inherent in the non-linear properties of wind turbines (WTs); therefore, they achieve excellent performance and enhance the operation of the WT. Small-scale WTs are efficient and cost-effective; they are usually installed close to where the generated electricity is used. This technology is gaining popularity worldwide for off-grid electricity generation, such as in rural homes, farms, small factories, and commercial properties. To enhance the efficiency of the WT, it is vital to operate the WT at its maximum power. This work proposes an efficient and fast maximum power point tracking (MPPT) technique based on the SCT to eradicate the drawbacks of the conventional methods and enhance the operation of the WT at the MPP regardless of wind speed and load changes. The SCT has advantages, such as robustness, simplified design, fast response, no requirement for knowledge of WT characteristics, no need for wind sensors or intricate power electronics, and straightforward implementation. Furthermore, it improves speed convergence with minimal steady-state oscillations at the MPP. The investigated configuration involves a wind-driven permanent magnet synchronous generator (PMSG), uncontrolled rectifier, boost converter, and variable load. The two converters are used to integrate the PMSG with the load. Three scenarios (step changes in wind speed, stochastic changes in wind speed, and variable electrical load) are studied to assess the SCT. The results prove a high performance of the suggested MPPT control method for a fast convergence speed, boosted WT efficacy, low oscillation levels, and applicability under a variety of environmental situations. This work used the MATLAB/Simulink program and was then implemented on a dSPACE 1104 control board to assess the efficacy of the SCT. Furthermore, experimental validation on a 1 kW Darrieus-type WT driving a PMSG was performed.
Order analysis is a powerful technique for analysing the vibration signals of rotating machinery under a known variable rotational speed. It requires the installation of speed-measuring devices; however, these devices cannot be installed in most machines due to design or cost reasons. In this study, a new method based on a time delay and resampling technique is introduced to estimate the instantaneous frequency (IF) of the vibration signal of a gear system. Order analysis techniques are used to extract the gear fault features. The performance of the proposed method is validated using simulated data from a gear system under speed-up and speed-down conditions.
This paper proposes a new approach for the identification of a DC machine (DCM) parameters to build a mathematical model considering different dynamic regimes, which characterize the operation of the studied machine. The proposed solution is simple and is based on the combination of classical identification methods and those available in the identification toolbox of MATLAB. The results obtained experimentally are significantly better and clearly show that the proposed approach is simple to implement and the DCM model is obtained quickly with a reasonable accuracy.
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