Model-Free Predictive Current Control Strategy Considering Noise Error Compensation

Aiming at dependence about traditional model-free predictive control (MFPC) methods on the accuracy of current gradients, the essay puts forward a MFPC way using second order generalized integrator (SOGI), which improves the accuracy of current gradients from two aspects. Firstly, the current gradient look-up table is refreshed at each control moment by using the sampled current information, and the current prediction at the external time is realized by combining the updated current gradient, which reduces the influence of the traditional MFPC method update stagnation. Secondly, by analyzing the influence of measurement noise such as switching noise and environmental noise on the accuracy of the current gradient, a SOGI is designed and employed to compensate error of current gradient, enhance the reliability of current gradient, then improve output current property. Conclusively, simulation waveforms certifies efficacy of the given method in enhancing robustness of parameters and suppressing the influence of noise.