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Nonlinear modeling and identification method of fractional order permanent magnet synchronous motor

A permanent magnet synchronous motor and identification method technology, applied in the field of modeling and identification, can solve the problems of reducing motor performance, inapplicability to nonlinear systems, loss of dynamic characteristics, etc., to achieve the effect of high precision

Active Publication Date: 2020-03-17
DALIAN MARITIME UNIVERSITY
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AI Technical Summary

Problems solved by technology

Simplifying the permanent magnet synchronous motor into a linear model will lose the original dynamic characteristics and greatly reduce the performance of the motor
At present, all the modeling and identification methods of fractional order permanent magnet synchronous motors are only in the linear field, and are not suitable for nonlinear systems.

Method used

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  • Nonlinear modeling and identification method of fractional order permanent magnet synchronous motor
  • Nonlinear modeling and identification method of fractional order permanent magnet synchronous motor
  • Nonlinear modeling and identification method of fractional order permanent magnet synchronous motor

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Embodiment approach

[0066] As a preferred implementation manner, the step S5 also includes the following steps:

[0067] S51: Determine decision variables and constraints. The decision variable is order and parameters The variation range of the order is (0.5,1.5).

[0068] S52: Establish an optimization model according to the objective function:

[0069]

[0070] Among them, the amount of data collected by N, x k and are the states collected for the actual system and the estimated system at the kth moment, respectively.

[0071] S53: Convert the variable into a binary string through encoding, the precision is four digits after the decimal point, and it is calculated with the following formula: b j 、a j Represents the upper and lower bounds of the decision variable;

[0072] S54: Determine the decoding method and use the formula to decode;

[0073] S55: Determine the individual fitness evaluation method. Since the objective function is to take the minimum value, here the individ...

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Abstract

The invention provides a nonlinear modeling and identification method of a fractional order permanent magnet synchronous motor. The method comprises the following steps of establishing an electromagnetic torque and mechanical characteristic equation of a fractional order motor; converting a three-phase static coordinate system into a two-phase rotating coordinate system through the space vector transformation; establishing an estimation system model according to an actual system model; sampling the states of the actual system and the estimation system, and establishing an objective function; and searching the optimal combination of the independent variable order and the parameter of the objective function by using a genetic algorithm, so that the value of the objective function is minimum.Compared with a traditional modeling mode, the fractional calculus theory is adopted to establish a motor model, so that the model is closer to the actual characteristics of the motor, and the dynamic behavior of the motor can be described more accurately. A traditional motor identification method adopts a strategy that id =0, so that the motor is simplified into a linear system. The identification method of the present invention does not carry out linearization processing on the motor system, so that the precision of the established model is higher.

Description

technical field [0001] The invention relates to the technical field of modeling and identification methods, in particular, to a nonlinear modeling and identification method of a fractional-order permanent magnet synchronous motor. Background technique [0002] Permanent magnet synchronous motors (PMSMs) have been widely used in high-performance applications due to their high efficiency, high power density, small size, and simple structure. However, the permanent magnet synchronous motor system is a nonlinear, multivariable, and strongly coupled system. When it works under certain conditions, it produces chaotic behavior. The main manifestations are unstable speed, severe torque oscillation, decreased control performance, and irregular electromagnetic noise. For situations with high requirements such as low vibration, low noise and high precision, dynamic performance is the main aspect that people pay attention to. Most of the previous research results are concentrated in ...

Claims

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Application Information

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IPC IPC(8): G06F30/20G06F17/11
CPCG06F17/11
Inventor 王兴成鲁森魁李雅男王龙达
Owner DALIAN MARITIME UNIVERSITY
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