AC servo system rotation inertia identification method

Abstract

The invention provides an AC servo system load torque and rotation inertia identification method and aims to achieve the fine dynamic and static characteristics of highly accurate control of a servo system according to the effect on the system performance by the permanent magnet synchronous AC servo system load rotation inertia and load torque. The method adopting the load inertia and motor rotor inertia as an entire inertia, allowing a servo system to perform regular forward and reverse speed increasing and decreasing movement, adopting a load disturbance torque state observer to observe the load disturbance torque changes of the motor, acquiring a model disturbance torque, adopting the integration identification algorithm, and identifying the system rotation inertia through mathematical derivation.

Description

technical field [0001] The invention relates to an AC permanent magnet synchronous motor servo system, in particular to a method for identifying the moment of inertia of the AC permanent magnet synchronous motor servo system. Background technique [0002] In the permanent magnet synchronous motor servo system, when the motor load moment of inertia and load torque change, the performance of the optimized controller in the servo system will be seriously degraded, which greatly restricts the improvement of system performance. By accurately identifying the total moment of inertia and load torque of the current system, speed control with good transient characteristics can be achieved. It can be seen that the research on the moment of inertia identification function in high-performance AC servo systems is very important, especially the intelligent identification of the system's moment of inertia has very practical significance for the precise control of the servo system. It can a...

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Problems solved by technology

[0007] At home and abroad, a large number of experimental studies have been carried out on the identification of the moment of inertia of the AC servo system. The advantages and disadvantages of each method are summarized as follows: the discrete model refers to the adaptive theory, the identification error is large, and the convergence time is long; the recursive least squares with the forgetting factor The algorithm needs to use high-order filters, which increases the complexity of the algorithm, and requires a large amount of computing memory, which limits its scope of use. It is only suitable for some systems with relatively simple mathematical models, and is not suitable for complex objects; Kalman filter and the extended least squares method are suitable for linear systems, but due to the nonlinearity of the motor model, its identification algorithm will inevitably encounter nonlinear filtering problems, and the calculation amount of the algorithm is complex, and the convergence is related to the dynamic response of the motor, so it is not suitable Applied to real-time control with fast motor speed response

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