Stability-Oriented Design of Model Predictive Control for DC/DC Boost Converter
Yuan Li, Subham Sahoo, Tomislav Dragičević, Yichao Zhang, Frede Blaabjerg
Abstract
Model predictive control (MPC) based on long prediction horizons can address the inherent nonminimum phase (NMP) behavior issue of dc/dc boost converters. However, the response time of the controller will increase since the long prediction horizons result in a high computational burden. To solve this problem, an NMP behavior improving (NPI) MPC with a single prediction horizon is proposed in this article. First, the actual cause behind the NMP behavior is analyzed. Afterward, the difference equation is modified according to the analysis and then used in the NPI-MPC. In addition, a fixed switching frequency is generated based on the value of the duty cycle, which is realized in the NPI-MPC algorithm and a modulation. Moreover, a weighting factors design guideline based on the stability criterion of a Jacobian matrix is provided. It effectively reflects the impact and sensitivity of different weighting factors on stability. Finally, we conclude this article by validating the proposed NPI-MPC method and the weighting factors-design guidelines with the results obtained under experimental conditions.