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Finite-time neural network control method of motor-driven single-connection rod manipulator

A technology of neural network control and motor drive, which is applied in the direction of adaptive control, general control system, control/regulation system, etc., and can solve problems such as system uncertainty, dead zone input, output limitation, etc.

Inactive Publication Date: 2018-09-18
NORTHWESTERN POLYTECHNICAL UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] The purpose of the present invention is to provide a finite-time neural network control method for a motor-driven single-link manipulator to solve the problems of output limitation, dead zone, input saturation, and system uncertainty in the actual motor drive system.

Method used

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  • Finite-time neural network control method of motor-driven single-connection rod manipulator
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  • Finite-time neural network control method of motor-driven single-connection rod manipulator

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Embodiment

[0268] Example: Motor-driven single-link manipulator

[0269] Taking the motor-driven single-link manipulator as an example to illustrate the effectiveness of the above-mentioned finite-time neural network control method in realizing the ideal trajectory tracking of the driven single-link manipulator. Such as figure 1 As shown, the system consists of a motor and a single-link manipulator. The dynamic equation of the system is as follows:

[0270]

[0271] In the formula, q, Respectively represent the angular position, angular velocity and angular acceleration, I is the motor armature current, ΔI is the current interference, L is the armature inductance, R is the armature resistance, K B is the counter electromotive force coefficient, V is the input control voltage, y is the system output, limited to the open set Ω={y:|y|c},k c is a normal constant representing the limit boundary, with The expression of is as follows:

[0272]

[0273]

[0274]

[0275] In ...

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Abstract

The invention relates to a finite-time neural network control method of a motor-driven single-connection rod manipulator. The method comprises steps of (1) establishing a mathematical model of the motor-driven single-connection rod manipulator and an actuator nonlinear module with a dead zone and input saturation limitations; (2) determining a control target, wherein system output is capable of tracking reference output of the system within the infinite time, and the system output is kept in a limited range; (3) designing an infinite time neural network control law and achieving a control target; and (4) designing a barrier Lyapunov candidate function and analyzing stability of a closed loop system, and according to the stability analysis of the Lyapunov candidate function, determining control parameters of the designed control law. According to the invention, by considering limitation factors of input saturation limitations, the dead zone, output limitations and system indeterminancy,the control method can be well applied in an actual system. In addition, infinite-time track tracking can be achieved; tracking time is reduced; and robustness and control precision of the system areimproved.

Description

technical field [0001] The invention relates to the field of industrial control, in particular to a finite-time neural network control method for a motor-driven single-link manipulator. Background technique [0002] Precise control of electric motors is a key technology in many industrial applications. For motors, due to environmental barriers and safety restrictions and performance index requirements, the rotor position needs to be limited within a certain range, if the output limit is ignored during the controller design process, it will lead to system performance degradation and system damage , so the output limit needs to be considered when designing the controller. In addition, there will be non-smooth nonlinear limitations at the connection between the motor and the mechanical device, including dead zone and input saturation, which will reduce system performance and control accuracy, and even cause system instability. Therefore, in the design of control Deadband and ...

Claims

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Application Information

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IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 倪骏康
Owner NORTHWESTERN POLYTECHNICAL UNIV
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