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PMSM chaotic system neural network dynamic surface control method considering output constraints

A technology of dynamic surface control and neural network, applied in the direction of adaptive control, general control system, control/regulation system, etc., can solve problems such as not comprehensive consideration

Active Publication Date: 2019-10-18
GUIZHOU UNIV
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Problems solved by technology

[0002] As a typical mechatronic product, the permanent magnet synchronous motor has the advantages of simple structure, reliable operation, high power density, large torque inertia ratio and high torque-current ratio, and is widely used in aerospace, robotics, CNC machine tools, and vehicle engineering and other fields have been widely used, but they have not comprehensively considered the influence of factors such as uncertain unknown parameters and external disturbances on the performance of nonlinear permanent magnet synchronous motor systems.

Method used

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  • PMSM chaotic system neural network dynamic surface control method considering output constraints
  • PMSM chaotic system neural network dynamic surface control method considering output constraints
  • PMSM chaotic system neural network dynamic surface control method considering output constraints

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Embodiment 1

[0107] Embodiment 1: as Figure 1-Figure 5 As shown, a PMSM chaotic system neural network dynamic surface control method considering output constraints, the method includes the following steps:

[0108] (1) Establish the nominal dynamic model of the permanent magnet synchronous motor system:

[0109] The dynamic equation of the surface permanent magnet synchronous motor is expressed in the d-q coordinate system as

[0110]

[0111] In the formula: with Indicates d-axis and q-axis current, with Denotes d-axis and q-axis voltage as system input, L, R, ψ r , B, J and n p Represent inductance, rotor angular velocity, stator resistance, load torque, flux linkage, viscous friction coefficient, rotor moment of inertia and magnetic pole pair, simplify formula (1), and select n p = 1,x 1 =ω,x 2 = i q , x 3 = i d , then (1) can be simplified as:

[0112]

[0113] In the formula: σ 1 =BL / (JR),σ 2 =-n p ψ r2 / (BR) where x 1 = ω,x 2 = i q ,x 3 = i d ...

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Abstract

The invention discloses a PMSM chaotic system neural network dynamic surface control method considering output constraints. The PMSM chaotic system neural network dynamic surface control method considering the output constraints comprises the following steps: 1) establishing a dynamic model of a PMSM system; and 2) using a kinetic model to build an adaptive dynamic surface controller; using the RBF network to approximate a nonlinear unknown term, a nonlinear term and a nonlinear damping term of the system model to overcome external disturbances; and introducing a first-order low-pass filter toreplace the derivative of the virtual control through the dynamic surface defined by a nominal motor speed of the nominal dynamic model and an ideal trajectory signal. The PMSM chaotic system neuralnetwork dynamic surface control method considering the output constraints disclosed by the invention can effectively suppress the influence of unknown parameters, chaotic oscillations and external disturbances on the system; and meanwhile, the output is constrained within a specified range, therefore, the invention has good validity and robustness.

Description

technical field [0001] The invention relates to a PMSM chaotic system neural network dynamic surface control method considering output constraints, and belongs to the technical field of permanent magnet synchronous motor control methods. Background technique [0002] As a typical mechatronic product, the permanent magnet synchronous motor has the advantages of simple structure, reliable operation, high power density, large torque inertia ratio and high torque-current ratio, and is widely used in aerospace, robotics, CNC machine tools, and vehicle engineering and other fields have been widely used, but they have not comprehensively considered the influence of factors such as uncertain unknown parameters and external disturbances on the performance of nonlinear permanent magnet synchronous motor systems. Contents of the invention [0003] The technical problem to be solved in the present invention is: provide a kind of PMSM chaotic system neural network dynamic surface contr...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 张钧星王时龙李少波罗绍华张星星
Owner GUIZHOU UNIV
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