Neural network and active disturbance rejection composite control method for three-axis tripod head servo motor

An active disturbance rejection controller and neural network technology, applied in the direction of DC motor speed/torque control, control system, control of multiple DC motors, etc., can solve the difficulty of PID control to achieve high-precision control, and the strong friction of the servo motor of the pan/tilt And other issues

Inactive Publication Date: 2019-04-16
GUANGXI NORMAL UNIV
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  • Abstract
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Problems solved by technology

Since the friction phenomenon in the servo system exists objectively, the pan/tilt servo motor will have a strong friction phenomenon when it is running at low

Method used

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  • Neural network and active disturbance rejection composite control method for three-axis tripod head servo motor
  • Neural network and active disturbance rejection composite control method for three-axis tripod head servo motor
  • Neural network and active disturbance rejection composite control method for three-axis tripod head servo motor

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Embodiment

[0062] The principle block diagram of the three-axis pan-tilt control strategy in this embodiment is as follows figure 1 As shown, the servo motors of the yaw axis, roll axis and pitch axis use DC motors as the actuators, and the output shafts of the motors are directly connected to the frame, where the pitch axis is connected to the inner frame, the roll axis is connected to the middle frame, and the yaw axis is connected to the middle frame. frame connected. The stability of the inner frame has the greatest impact on the imaging quality. In this embodiment, the control of the inner frame is taken as an example, and each axis and frame are controlled by the method of this embodiment.

[0063] A kind of compound control method of neural network and self-disturbance rejection of three-axis pan-tilt servo motor, comprising the following steps:

[0064] 1) Establish the dynamic equation of the three-axis gimbal inner frame servo system with the Stribeck friction model:

[0065]...

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Abstract

The invention discloses a neural network and active disturbance rejection composite control method for a three-axis tripod head servo motor. The method is characterized by comprising following steps of (1) establishing a three-axis tripod head internal frame servo system dynamical equation with a Stribeck friction model, (2) designing an active disturbance rejection controller for the dynamical equation established in step (1), and (3) designing an RBF neural network, combining the RBF neural network with the active disturbance rejection controller to form an RBF neural network active disturbance rejection supervisory controller. According to the method, better response speed and control accuracy can be achieved in a nonlinear system, the stability and robustness of a control system can beensured, the introduction of neural network can improve the adaptive ability of the system, and the method can adapt to a larger range of a controlled object under the condition of satisfying controlperformance requirements.

Description

technical field [0001] The invention relates to the technical field of three-axis pan / tilt servo motor control, in particular to a method for combining an RBF neural network with an ADRC (Active Disturbance Rejection Control, referred to as ADRC) to form an RBF neural network ADRC supervisory control method , especially a compound control method of neural network and active disturbance rejection for a three-axis pan-tilt servo motor. Background technique [0002] For the three-axis gimbal, how to design a good stabilization control method to counteract external shaking, so as to effectively overcome the image blur caused by lens shaking, is of great significance for obtaining high-quality images. In terms of spatial structure, the three-axis gimbal mainly consists of outer frame, middle frame, and inner frame, and the outer frame, middle frame, and inner frame are independent and perpendicular to each other, and have degrees of freedom in three directions. Assuming that the...

Claims

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Application Information

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IPC IPC(8): H02P7/00H02P5/68
CPCH02P5/68H02P7/00
Inventor 刘欣罗晓曙戴沁璇
Owner GUANGXI NORMAL UNIV
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