Model reference self-adaptive system parameter self-tuning method based on one-dimensional fuzzy control

An adaptive system and parameter self-tuning technology, applied in control systems, vector control systems, control generators, etc., can solve the problems of rotor position error, inability to obtain accurate rotor position information, inconvenience, etc., and achieve rotor position angle The effects of error reduction, good dynamic and static performance, and low system cost

CN103997274AActive Publication Date: 2014-08-20TSINGHUA UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2014-08-20

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Abstract

The invention relates to a model reference self-adaptive system parameter self-tuning method based on one-dimensional fuzzy control. The method comprises the following steps that (1) a model reference self-adaptive system based on the one-dimensional fuzzy control is structured according to an actual physical model of a permanent magnet synchronous motor; (2) direct-axis currents and quadrature-axis currents are calculated respectively according to the actual model and a reference model, and a current error variable e(t) of the direct-axis currents and the quadrature-axis currents is obtained according to an error calculation formula; (3) the changing range of e(t) is defined as current error variable pulsation band e(t)band, and the e(t)band is sent into a one-dimensional fuzzy controller after action of the input scale factor Ke of the one-dimensional fuzzy controller; (4) fuzzy controlled quantity output u(t) is obtained according to one-dimensional fuzzy rules; (5) u(t) is acted by the output scale factor Ku of the one-dimensional fuzzy controller and amplified to the actual controlled quantity on PI parameters; (6) u(t) is converted into a precise output value u0(t) and is overlapped on the PI parameters. The model reference self-adaptive system parameter self-tuning method based on the one-dimensional fuzzy control can be widely applied to the field of control over motors without position sensors.
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Description

technical field

[0001] The invention relates to a motor control method, in particular to a model reference adaptive system parameter self-tuning method based on one-dimensional fuzzy control. Background technique

[0002] The model reference adaptive system is widely used in the control of speed sensorless permanent magnet synchronous motors because of its simple structure and easy implementation. At present, in the traditional model reference adaptive system, the PI (proportional-integral) controller can usually get good control performance when applied to the constant load condition, but when applied to the pulsating compressor load condition, the constant A single PI controller cannot meet the requirements of control performance well. The reason is that in the permanent magnet synchronous motor driven compressor system using the model reference adaptive system, the estimated rotor speed fluctuation is largely affected by the PI parameters in the model reference adaptive ...

Examples

Embodiment Construction

[0034] Specific embodiments of the present invention will be further described below.

[0035] In the traditional model reference adaptive system, the current error variable e(t) is obtained through the adaptive rate to identify the rotational speed. The present invention adopts a non-linear self-adaptive law based on fuzzy logic to replace the PI controller in the rotational speed observer of the traditional model reference self-adaptive system, and e(t) obtains the identification rotational speed directly through the one-dimensional fuzzy controller.

[0036]The self-tuning method of model reference self-adaptive system parameters based on one-dimensional fuzzy control of the present invention comprises the following steps:

[0037] 1) According to the actual physical model of the permanent magnet synchronous motor, refer to the traditional model reference adaptive system (such as figure 1 shown), construct a model reference adaptive system based on one-dimensional fuzzy co...