PMSM chaotic system neural network inversion control method

A neural network and inversion control technology, which is applied in the field of PMSM chaotic system neural network inversion control, can solve problems such as reducing the stability of the system operation

Active Publication Date: 2019-10-15
GUIZHOU UNIV
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Problems solved by technology

Various dynamic behaviors such as chaos, parameter perturbation and time delay will reduce the stability of the system operation

Method used

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  • PMSM chaotic system neural network inversion control method
  • PMSM chaotic system neural network inversion control method
  • PMSM chaotic system neural network inversion control method

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Embodiment 1

[0182] Embodiment 1: as Figure 1-Figure 6 Shown, a kind of PMSM chaotic system neural network inversion control method, this method comprises the following steps:

[0183] (1) Establish dynamic model of permanent magnet synchronous motor system:

[0184] In the rotating (d-q) coordinate system, the dynamic equation of the permanent magnet synchronous motor system is expressed as:

[0185]

[0186] In the formula: and Indicates d-axis and q-axis current, and Indicates d-axis and q-axis voltages as system input, 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 ,L=L d = L q ,make σ 1 =BL / (JR),σ 2 =-n p ψ r 2 / (BR) and Equation (1) is simplified to the following nominal kinetic model:

[0187]

[0188] Where: x 1 ,x 2 ,x 3 ,t,T L , u d and u ...

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Abstract

The invention discloses a PMSM chaotic system neural network inversion control method, which comprises steps: 1) a dynamic model of the PMSM system is built; 2) a robust neural network adaptive tracking controller is built, system output tracking errors have set performance constraints, a non-strict feedback control structure and a PP-TBLF are combined, the controller for the permanent magnet synchronous motor system adopts the neural adaptive tracking control scheme of the inversion technique, during a recursive process, a Chebyshev neural network, Lyapunov functional, Nussbaum functional anda differential tracker are used respectively to process unknown nonlinearities, time delay, unknown gain symbols, and complexity explosions. The system stability can be realized, and the versatilityand the reliability of the system are enhanced.

Description

technical field [0001] The invention relates to a PMSM chaotic system neural network inversion control method, belonging to the technical field of permanent magnet synchronous motor control methods. Background technique [0002] Permanent Magnet Synchronous Motor (PMSM) systems are in increasing demand in many industrial equipment sectors such as automotive, machine tools, robotics and aerospace. The dynamic behavior control of PMSM system has always been a hot issue in the current academic circles. Various dynamic behaviors such as chaos, parameter perturbation and time delay will reduce the stability of system operation. Contents of the invention [0003] The technical problem to be solved by the present invention is to provide a PMSM chaotic system neural network inversion control method to solve the above-mentioned problems in the prior art. [0004] The technical scheme that the present invention takes is: a kind of PMSM chaotic system neural network inversion contr...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02P21/00
CPCH02P21/0014H02P2207/05
Inventor 张钧星罗绍华王时龙李少波周鹏
Owner GUIZHOU UNIV
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