Stochastic Programming Based Objective Function Optimization for Predictive Thrust Control of Linear Induction Machine
Publication Name
Conference Record - IAS Annual Meeting (IEEE Industry Applications Society)
Abstract
Model predictive thrust control (MPTC) is one of the most effective approaches for linear induction motor (LIM) drive system. It can achieve the optimization of multiple objectives. However, the process of tuning the weighting factors in the objective function is the main drawback of MPTC. It greatly increases the computation burden. In this paper, the tuning process of weighting factors is regarded as a random sampling process. Then, a novel weighting factor optimization method based on the stochastic programming technique is proposed to select the suitable control action for LIM. It will optimize with flux and thrust together to avoid the adjustment of weighting factor. In this paper, the optimal model can be solved by Monte Carlo simulation. At last, the simulation results have shown better dynamic and steady state performance of the proposed method.
Open Access Status
This publication is not available as open access
Volume
2021-October
Funding Number
2019AAA026
Funding Sponsor
National Natural Science Foundation of China