Reinforcement learning controller for five-degree-of-freedom bearingless permanent magnet synchronous motor and construction method thereof

Abstract

The invention discloses a reinforcement learning controller for a five-degree-of-freedom bearingless permanent magnet synchronous motor and a construction method thereof. The reinforcement learning controller is composed of a current control module, six differentiators and three actor-critic modules, wherein an output of the three actor-critic modules is connected with a bearingless permanent magnet synchronous motor system via the current control module. According to the controller and the construction method thereof, the actors and critics in reinforcement learning in the field of artificial intelligence is combined with a traditional vector control technology, the critic evaluates rotation speed and displacement feedback information of a five-degree-of-freedom motor system and guides the actuator to output each current of the motor, a controller parameter can be online updated without an accurate motor model, stable operation of the motor can be maintained, strong capacities of resisting motor parameter variation and load disturbance are provided, meanwhile influences of uncertain factors, such as system parameter variation and load sudden change, on the system performance are overcome, and better robustness is provided.

Description

technical field [0001] The invention belongs to the technical field of electric drive control equipment, relates to a controller structure and a construction method of a five-degree-of-freedom bearingless permanent magnet synchronous motor, and is suitable for high-performance control of a five-degree-of-freedom bearingless permanent magnet synchronous motor. Five-degree-of-freedom bearingless permanent magnet synchronous motors are widely used in many high-speed and ultra-high-speed special electric transmission fields such as centrifuges, sealed pumps, aerospace, CNC machine tools, flywheel energy storage, and life sciences. Background technique [0002] The five-degree-of-freedom bearingless permanent magnet synchronous motor consists of a two-degree-of-freedom bearingless permanent-magnet synchronous motor and a three-degree-of-freedom hybrid magnetic bearing. It is a multivariable, strongly coupled nonlinear complex system. The five-degree-of-freedom bearingless permane...

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Problems solved by technology

[0006] The purpose of the present invention is to solve the problem that the self-adaptive control of the existing five-degree-of-freedom bearingless permanent magnet synchronous motor control requires an accurate mathematical model, solve the problem that the existing single neural network controller needs to read training data in advance, and perform a large number of offline training , once the weight value is fixed, it cannot be adjusted online. An adaptive reinforcement learning controller is proposed to make the five-degree-of-freedom bearingless permanent magnet synchronous motor have excellent dynamic and static control performance. At the same time, the structure of the reinforcement learning controller is proposed method

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