Predictive control error correction method based on cascaded multilevel inverter

Abstract

The invention provides a predictive control error correction method based on a cascaded multilevel inverter. The method comprises the following steps of: S1, building a mathematical model based on the topological structure of the cascaded multilevel inverter; establishing a discretization prediction model which comprises a capacitor voltage prediction model and a current prediction model; S2, establishing a capacitor voltage prediction error correction model, capacitor voltage prediction errors comprising a capacitor voltage prediction error caused by capacitor parameter mismatch, a capacitor voltage prediction error caused by model discretization and a capacitor voltage prediction error caused by sampling; S3, establishing a current prediction error correction model, current prediction errors comprising a current prediction error caused by capacitor parameter mismatch, a current prediction error caused by model discretization and a current prediction error caused by sampling; S4, obtaining a solution of the capacitor voltage prediction error; and S5, obtaining the solution of the current prediction error. According to the method of the invention, error correction can be completed.

Description

technical field [0001] The invention relates to a control method, in particular to a method for correcting prediction control errors based on cascaded multilevel inverters. Background technique [0002] Cascaded multilevel inverters have always been favored in medium-high voltage and high-power applications because of their simple structure, easy modular design, high-quality output waveforms, and easy implementation of redundancy. In industrial applications, triangular carrier PWM (TCPWM) and space vector PWM (SVPWM) methods are often used to control multilevel inverters. However, with the development of microprocessors, more advanced model predictive control (Model predictive control, MPC) It is possible to apply it in cascaded multilevel inverters. [0003] Compared with the traditional PI control method, model predictive control has higher dynamic performance and stronger robustness. Especially for multi-variable and multi-constrained systems such as multi-level topolog...

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Problems solved by technology

The main problem with this type of solution is that it requires multiple or multiple cycles of calculation, and the process is complicated

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