Optimal two-vector combination-based model predictive control method and system

A technology of model predictive control and vector combination, applied in vector control system, control system, control generator, etc., can solve problems such as large amount of calculation and large current ripple

Active Publication Date: 2017-05-31
HUAZHONG UNIV OF SCI & TECH
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Problems solved by technology

This solves the technical problems of large current ripple and large

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  • Optimal two-vector combination-based model predictive control method and system
  • Optimal two-vector combination-based model predictive control method and system
  • Optimal two-vector combination-based model predictive control method and system

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[0044] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other.

[0045] figure 1 It is a structural diagram of a PMSM control system based on the MPC method of the present invention. The system uses i d * =0 control mode, speed loop uses PI controller, output as stator current reference value i q * . Sampling motor rotor speed ω, position signal θ, stator current i abc and DC bus voltage U dc , combined with the switch state S abc Calculate the curre...

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Abstract

The invention discloses an optimal two-vector combination-based model predictive control method and system. The method is applied to a permanent-magnet synchronous motor control system driven by a three-phase two-level inverter. A model predictive current control strategy is adopted, all two-vector combinations and resultant vector sets obtained under action time are considered at the same time, and a cost function is inspected and an optimal resultant vector is selected from all to-be-selected sets. In order to simplify the optimization process, an equivalent voltage equation is given, a sector transformation method is provided and to-be-selected two-vector combination sets are transformed into multiple fixed line segments; and a fast algorithm is given and partial complicated calculation is transformed to offline execution, so that the real-time calculated amount of the novel method is effectively reduced. The model predictive control method disclosed by the invention is simple in structure, small in real-time calculated amount and easy to implement; and the response speed of a motor is high, current ripples and distortion are small, the switching frequency is low and the dynamic and static performance of the system is excellent.

Description

technical field [0001] The invention belongs to the technical field of industrial automation, and more specifically relates to a model predictive control method and system based on optimal two-vector combination. Background technique [0002] At present, there are many kinds of AC motor control techniques, such as vector control, direct torque control, sliding mode control and fuzzy control. However, the above control methods all have certain deficiencies, such as slow dynamic response of vector control, unsatisfactory low-speed characteristics of direct torque control, and large torque ripple. Model Predictive Control (MPC) was born in the 1970s. With the rapid development of computer technology and microcontrollers, its application in real-time fast dynamic systems has become a research hotspot in recent years. MPC is applied to the permanent-magnet synchronous motor (Permanent-Magnet Synchronous Motor, PMSM) control system, which can significantly improve the system resp...

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Application Information

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IPC IPC(8): H02P21/00H02P21/22H02P21/14H02P25/022
CPCH02P21/0017H02P21/14
Inventor 程善美刘莹刘江
Owner HUAZHONG UNIV OF SCI & TECH
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