An Improved Model-Free Predictive Current Control With Advanced Current Gradient Updating Mechanism

Model-based predictive control that highly depends on system parameters is widely investigated. In contrast, model-free current (MFPCC) can be performed based input or output measured data, rather than any model information, hence eliminating the influence of parameter uncertainties. such a strategy, gradients due to each possible voltage vectors are stored and used predict future currents. Current gradient knowledge therefore provides significant foundation for MFPCC. conventional MFPCC, however, stagnation existing in update always impacts reliability further worsens performance. this article, an improved MFPCC with advanced updating mechanism proposed. proposed guarantee gradients, two contiguous applied estimate all vectors. This simple method takes advantage mathematical relationships between way, obtained within one period, effectively reducing effect The scheme evaluated permanent magnet synchronous machine drive setup demonstrate its effectiveness.