Generalized Multiple-Vector-Based Model Predictive Control for PMSM Drives

Improved Optimization Process for Nonlinear Model Predictive Control of PMSM

Model-based predictive control (MPC) is one of the most efficient techniques that is widely used in industrial applications. In such controllers, increasing the prediction horizon results in better selection of the optimal control signal sequence. On the other hand, increasing the prediction horizon increase the computational time of the optimization process which make it impossible to be imple...

Fuzzy Rule – Based Model Reference Adaptive Control for PMSM Drives

The objective of the model reference adaptive fuzzy control (MRAFC) is to change the rules definition in the direct fuzzy logic controller (FLC) and rule base table according to the comparison between the reference model output signal and system output. The MRAFC is composed by the fuzzy inverse model and a knowledge base modifier. Because of its improved algorithm, the MRAFC has fast learning ...

Combined Speed and Current Model Predictive Control for energy-efficient PMSM Drives

The paper deals with the Model Predictive Control (MPC) algorithm applied to control a permanent magnet synchronous motor, which is, at present, among the motors with the highest power efficiency and then very attractive for energy–saving applications. Absolute novelty of the proposed MPC is its feature of inherently managing the flux weakening control above base speed. Speed and current contro...

Model-Based Predictive Control of Electrical Drives

Intelligent Model-Following Position Control for PMSM Servo Drives

In this paper, an intelligent robust position controller for permanent-magnet synchronous motor (PMSM) servo drives is proposed. The intelligent robust position controller consists of a two-degrees-offreedom integral plus proportional & rate feedback (2DOF I-PD) controller in addition to an on-line trained neural-network model-following controller (NNMFC). This controller, 2DOF I-PD NNMFC, comb...