An electric motor control device and an electric motor control system

Abstract

The invention provides an electric motor control device and sets best gain reduction for the input signals provided to the recognition operation. The invention comprises zero holding components (26, 27) for the periodical sampling and maintaining, delay components (28, 29) for the first sampling periodical delaying for the output signals of the zero holding components, multipliers (30, 31) for the reduction of the output signals of the delay components, a regression vector generation part (33) for the regression vector generation by adopting the output signals of the multipliers as the input, a discrete system parameter estimation part (34) for the discrete estimation of the parameter vectors by adopting the regression vector as the input and an automatic gain control part (32) which adopts the output signals of the zero holding components (26, 27) as the input signals and outputs the gain set values of the multipliers.

Description

technical field [0001] The invention relates to a motor control device and a motor control system for speed control by identifying parameters. Background technique [0002] As a motor control device used in industrial machinery (semiconductor manufacturing equipment, machine tools, injection molding machines), etc., a technique is known to identify the total moment of inertia, viscous friction coefficient, constant external disturbance torque, etc. during actual operation Mechanical system parameters, and use the identification results for the automatic setting of controller parameters such as speed controllers. For example, Patent Document 1 discloses a technique for identifying the above-mentioned mechanical system parameters by the recursive least square method using time-series data of each motor torque, acceleration, and motor speed during forward rotation and reverse rotation. [0003] In addition, as a more general automatic setting technique of control parameters, s...

AI Technical Summary

Problems solved by technology

[0008] In the technique of the UD decomposition algorithm, when the absolute value of the input signal given to the recognition operation is too large, overflow may occur in the recursive least squares operation

In particular, due to the low dynamic range of values ​​that can be represented by fixed decimal point operations, overflow is prone to occur in the case of performing recursive least squares

[0009] For this problem, the general solution is to put an attenuator (attenuation gain greater than 0 and less than 1) on the input part of the recursive least squares method, but there are the following problems: when the attenuation gain is too large (attenuation rate is small) , the recognition error increases due to overflow; the attenuation gain is too small (the attenuation rate is large), and the recognition error caused by the rounding error of the input signal increases

In addition, as another solution, although there is a simple method of using a limiter on the calculation result to avoid overflow, it will also cause calculation errors caused by saturation, resulting in a problem of low recognition accuracy

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