Model parameter adaptive method for inverter model prediction control

Abstract

The invention discloses a model parameter adaptive method for the inverter model prediction control, and the method comprises the steps: firstly substituting system parameters calculated at a last moment into a prediction model, and calculating prediction current values corresponding to all vectors; secondly building a cost function according to a control requirement, selecting an optimal vector which enables the cost function to be minimum, and applying the optimal vector to a control system; thirdly carrying out the online correction of parameters in the model through voltage and current measurement values at this moment and all parameter values at the last moment after the optimal vector is selected. If inductance and resistance and other parameters need to be corrected on line, the method can correct the parameters at different moments so as to avoid excessive calculation burden caused by formula iteration. After the model prediction control is finished, a parameter recognition algorithm is added, and the method carries out the online correction of all parameters in the model through the prediction model of the system, and improves the operation robustness and control flexibility of an inverter.

Description

technical field [0001] The invention belongs to the technical field of inverter control and parameter identification, and in particular relates to a model parameter adaptive method for inverter model predictive control. Background technique [0002] In recent years, with the continuous progress and development of science and technology, whether in the field of modern industry or in the field of national defense technology, the operating environment of the system has become more and more complex, and people have higher and higher requirements for the accuracy of system control. For example, the missile defense system in the national defense system has an extremely complex and harsh working environment, and has very strict requirements for its rapid response capability and precise tracking capability. [0003] In some industrial control systems with strong nonlinearity, such as industrial servo systems and aircraft control systems, due to the current limited understanding of c...

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Problems solved by technology

[0004] Although there have been more and more researches on system parameter adaptation in recent years, and the identification of system parameters through various methods has become more and more accurate. However, most methods require an additional independent program, and the process of parameter adaptation is relatively complicated. , if parameter identification is performed online, more resources will be wasted

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