Multi-level matrix converter control method based on extended state observer

Abstract

The invention provides a multi-level matrix converter control method based on an extended state observer. The multi-level matrix converter control method comprises the following steps: establishing a mathematical model of an M3C; carrying out double alpha beta 0 transformation to obtain a decoupling mathematical model of the M3C; writing an M3C mathematical model in an alpha beta 0 coordinate system into a hyperlocal model form; and designing an extended state observer for estimating uncertain items in the hyper-local model, calculating the voltage of an M3C reference bridge arm by using a deadbeat algorithm based on the obtained extended state observer, and generating a switch state combination of sub-modules in the bridge arm according to a modulation algorithm. An extended state observer is designed to carry out real-time estimation on unmodeled dynamics and external disturbance in an M3C system, a super-local model of the M3C is utilized to carry out control, and the method has a model-free control characteristic. Therefore, the robustness of the system facing working conditions such as external disturbance and parameter mismatch can be improved, the defect that a traditional dead-beat control strategy depends on an accurate mathematical model of the converter is overcome, and rapid dynamic response and good steady-state performance can be obtained.

Description

technical field [0001] The present application relates to the field of converter control, and in particular, to a multi-level matrix converter control method based on an expanded state observer. Background technique [0002] Modular Multilevel Matrix Converter (M3C) is a multi-level converter that combines Modular Multilevel Converter (MMC) and Matrix Converter (MC). Orthogonal transformation topology. Due to the cascading structure, modular design, and many advantages of multi-level converters, it has broad application prospects in high-voltage large-capacity AC-to-AC conversion systems. [0003] In order to meet the control requirements of M3C in different scenarios, different control algorithms have been proposed successively, such as fuzzy control, synovial control, and predictive control. However, the control performance of the above algorithms largely depends on the accuracy of the control object model. Due to the complex topology structure and large number of circui...

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Problems solved by technology

However, the control performance of the above algorithms largely depends on the accuracy of the control object model. Due to the complex topology of M3C and the large number of circuit devices, it is difficult to deal with uncertainties such as parameter mismatch and external disturbance in system modeling. Overcome, so it affects the control accuracy of the high-performance control algorithm, and in severe cases, it will cause system instability

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