A New Dimension Elimination Method and Robustness Research of Model Predictive Thrust Control of Linear Induction Motor Driven by Three-level Inverter

Model predictive control achieves different optimal control objectives, such as low ripple, high dynamic performance, low energy loss, and high robustness of linear induction motors. The difficulty of multi-objective control lies in adjusting the weighting factors between different physical quantities. Currently, the most commonly used method is the online table lookup method, which selects the optimal weighting factor by enumerating a large number of cases. However, this method takes a long time to search, has a large computational burden, and has slow dynamic response. In this paper, a new method is proposed to achieve dimension elimination and automatic weighting factor adjustment. This method has two objective functions. The first objective function defines the fluctuation suppression coefficient k p , which outputs a series of voltage vectors to suppress system instability. In the second function, the ripple amount is divided by the reference value based on the essence of the ripple. The fluctuation is defined as a relative concept, eliminating the dimension of a single target. The weighting factor can be selected as 1, avoiding the need for adjustment of the weighting factor. This method has been successfully applied in the Simulink simulation platform. The simulation results show that it not only greatly improves the robustness of the system but also avoids complicated weighting factor adjustment.