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RBF neural network generalized inverse internal model control method of linear motor

A linear motor and neural network technology, applied in the field of power transmission, can solve the problems of poor anti-interference ability of permanent magnet linear motors, and achieve the effect of superior key performance

Active Publication Date: 2016-11-16
SUQIAN COLLEGE
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Problems solved by technology

[0005] Aiming at the characteristics of poor anti-interference ability of permanent magnet linear motors, the present invention provides a linear motor RBF neural network generalized inverse internal model control method, which can effectively overcome the influence of disturbance signals and uncertain environments on the control system, and improve the performance of permanent magnet linear motors. Dynamic response capability and robustness

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  • RBF neural network generalized inverse internal model control method of linear motor
  • RBF neural network generalized inverse internal model control method of linear motor

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[0015] Now in conjunction with the accompanying drawings, the examples of the present invention will be described in detail.

[0016] Such as figure 1 As shown, the linear motor RBF neural network generalized inverse internal model control method includes: generalized inverse system, linear motor system, PI regulator, PD regulator, internal model controller, and coordinate transformation module. The generalized inverse system includes: RBF neural network generalized inverse module, current loop first-order integral module, speed loop second-order integral module; linear motor system includes: SVPWM modulation module, inverter, linear motor module.

[0017] The output end of the linear motor is measured and calculated by the photoelectric rotary encoder and the transformer used to detect the phase current to obtain the rotational speed ω r , electrical angle θ, phase current i a i b i c . The two rotating coordinate currents obtained by changing the coordinates of the pha...

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Abstract

The invention discloses an RBF neural network generalized inverse internal model control method of a linear motor. A generalized inverse system of a permanent magnet linear motor free of an accurate mathematical model is approached through an RBF neural network; and the generalized inverse system is connected with a permanent magnet linear motor system in series, so that linearization and decoupling of a permanent magnet linear motor control system are achieved; and through correction on a decoupled pseudo linear system through inner model control, the key properties of the control accuracy, the dynamic response capability, the robustness and the like of the permanent magnet linear motor control system are more excellent.

Description

technical field [0001] The invention relates to a generalized inverse internal model control method of a linear motor RBF neural network, which belongs to the technical field of electric transmission. Background technique [0002] Linear motors can directly convert electrical energy into mechanical energy of linear motion, which not only saves the intermediate transmission mechanism, but also reduces system losses. It is widely used in servo control system. [0003] The permanent magnet linear motor also has the characteristics of sudden change of parameters with the change of operating state, nonlinear strong coupling and other characteristics. The control system has multiple inputs and multiple outputs and cannot obtain an accurate mathematical model. Therefore, traditional control theory cannot meet the control of modern high-performance linear motors. need. [0004] The neural network generalized inverse system takes into account the characteristics of linearization an...

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Application Information

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IPC IPC(8): H02P25/06H02P21/00
CPCH02P21/0014H02P25/06
Inventor 张锦茆正平仲伟松高磊孙延永
Owner SUQIAN COLLEGE
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