Disturbance-estimation-based model prediction control high-speed railway low frequency oscillation inhibition method

Abstract

The invention discloses a disturbance-estimation-based model prediction control high-speed railway low frequency oscillation inhibition method. The disturbance-estimation-based model prediction control high-speed railway low frequency oscillation inhibition method includes the following steps: A, constructing a D-series high-speed train network side rectifier dynamic characteristic equation considering the parameter error quantity under a d-q rotating coordinate system; B, defining the disturbance quantity, and according to the dynamic characteristic equation, obtaining a D-series high-speed train network side rectifier current prediction model considering the disturbance quantity under the d-q rotating coordinate system; C, taking the current and the disturbance quantity as state variables, obtaining a state space model of a disturbance estimator, and constructing the disturbance estimator; D, substituting a estimated value of the disturbance quantity into the current prediction model in the step B to obtain a current prediction value, and substituting the obtained current prediction value into a cost function to obtain the next sampling period control voltage; and E, obtaining an alpha-beta coordinate system component by performing coordinate transformation on the control voltage, and outputting the control pulse through sine pulse width modulation to complete high-speed railway low frequency oscillation inhibition. The disturbance-estimation-based model prediction control high-speed railway low frequency oscillation inhibition method can improve the anti-interference capability and the robustness performance of the control system, can minimum floating of the voltage variance in the period, and is not sensitive to change of parameters.

Description

technical field [0001] The invention relates to a control method for a rectifier on the grid side of a motor train, in particular to a method for suppressing high-speed rail low-frequency oscillation based on model predictive control based on disturbance estimation. Background technique [0002] With the rapid development of high-speed railways, the new "AC-DC-AC" electric locomotive has been widely used in electrified railway systems due to its advantages of high power factor, high power, and large traction; the traditional "AC-DC-AC" The control methods of locomotives are mainly divided into two categories, indirect current control and DC current control; indirect current control is represented by "phase-amplitude control", and direct current control includes hysteresis current control, predictive current control and transient current control; State direct current control is currently the most used control strategy in electric locomotives and high-speed EMUs; the control e...

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Problems solved by technology

[0002] With the rapid development of high-speed railways, the new "AC-DC-AC" electric locomotive has been widely used in electrified railway systems due to its advantages of high power factor, high power, and large traction; the traditional "AC-DC-AC" The control methods of locomotives are mainly divided into two categories, indirect current control and DC current control; indirect current control is represented by "phase-amplitude control", and direct current control includes hysteresis current control, predictive current control and transient current control; State direct current control is currently the most used control strategy in electric locomotives and high-speed EMUs; the control effect of traditional linear control methods has been difficult to improve, so nonlinear control methods, such as predictive control and passive control, are introduced The control of the converter is necessary; the predictive control is accompanied by the proposed control algorithm in the complex actual production process, and is widely used because of its good robustness and good complex system control performance; the commonly used model prediction Control includes predictive current control, predictive direct power control, etc. It only considers the predicted current obtained by the predictive model to track the set value to improve the control effect, but does not consider the problem that the parameters of the model parameters and the parameters of the actual controlled object cannot completely match

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