Data-Driven Predictive Control with Inherent Update Method for Two-Level Voltage Source Inverters
ID:143 View Protection:PUBLIC Updated Time:2023-06-13 20:32:46 Hits:419 Oral Presentation

Start Time:2023-06-18 09:30 (Asia/Shanghai)

Duration:20min

Session:[S] Oral Session » [S2] Oral Session 2 & Oral Session 5

Abstract
This paper proposes an inherent and effective method for updating the database which is critical for the model-free predictive controller. In contrast to existing update methods which require complex analytical expressions, a unified analytical update model is proposed as a sum of the actual current and input control gradients.  The effectiveness of the proposed controller is validated in a two-level voltage source inverter connected to the grid and an RLE load. The simulation results show that DDPC effectively cancels the stagnant mode and compared with MPC, DDPC provides better current performance at normal conditions and has higher robustness under parameter mismatches. 
Keywords
MODEL PREDICTIVE CONTROL;Model-free Predictive Control;voltage source converter
Speaker
Paul Gistain Ipoum Ngome
null

Mon-Nzongo Daniel

Tao Jin
Fuzhou University

Jinquan Tang

Jose Rodriguez
Universidad San Sebastian

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