Novel intelligent motor controller

Abstract

The present invention discloses a novel intelligent motor controller. The novel intelligent motor controller includes a controller, an input unit and a photoelectric encoder; the controller transmits signals to a motor through a driver and a Hall element, wherein the Hall element is used for detecting the phase current of the motor, carrying out A / D conversion on the phase current, and feeding back a conversion result to the controller, and the motor is connected with the controller through the photoelectric encoder; the input unit is used for parameter setting of the motor; the photoelectric encoder is used for converting the rotation angle of the motor into orthogonal electric pulse signals; the controller tracks the rotation position of the motor according to feedback electric pulse signals; and the controller calculates the error value of the position of the motor according to an inputted position value and an inputted position feedback value, and generates motor speed control signals through the driver. With the novel intelligent motor controller adopted, the dynamic and static control quality of a servo motor system can be improved.

Description

technical field [0001] The invention relates to the field of control, in particular to a novel intelligent motor controller. Background technique [0002] The AC servo motor has the advantages of simple structure, low cost, small size, light weight, large torque output, low inertia and good control performance. It can directly convert the control electrical signal into the mechanical rotation of the shaft, and the positioning accuracy of the servo motor It is quite high and has been widely used in automatic control systems and automatic detection systems as actuators. [0003] At present, many high-performance control algorithms have been proposed for the high-speed and high-precision requirements of the servo drive system at home and abroad. For example, the genetic algorithm is used to tune the parameters of the PID controller of the servo motor, although the ideal control effect can be achieved by using the genetic algorithm. However, the genetic algorithm itself has a ...

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Problems solved by technology

However, the genetic algorithm itself has a "premature" phenomenon, that is, the algorithm's ability to explore new spaces is limited, and it is easy to converge to a local optimal solution.

[0004] In the fuzzy logic algorithm, because the design of fuzzy rules requires strong engineering experience, the debugging process in the early stage takes a long time, and the selection of membership functions requires high requirements. Appropriate debugging methods and rich debugging experience are required. The dependence is strong, and the problem of establishing a knowledge base through machine learning needs to be studied

However, these control algorithms are based on the traditional hardware structure. The servo driver can only use a certain fixed control algorithm. The system cannot adjust the control algorithm and control parameters in real time according to the changes in the working environment and load status, and cannot give full play to the advantages of different control algorithms. Performance characteristics, in the positioning process of the servo motor, have a great influence on the positioning accuracy

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