A Distributed Adaptive Coordinated Control Method for Multi-Permanent Magnet Synchronous Motor

Abstract

The invention provides a distributed self-adaptive coordinated control method of multi-permanent magnet synchronous motors, comprising step 1. First establishing a dynamic model of a controlled system of n permanent magnet synchronous motors. Step 2. Design the distributed controller according to the communication relationship between the permanent magnet synchronous motors. Step 3. Utilize the local state information exchange between each node and its neighbor nodes that have a communication relationship, and design an adaptive law to achieve the goal of coordinating multiple permanent magnet synchronous motors. The invention proposes a distributed self-adaptive coordination control method for multiple permanent magnet synchronous motors, and accurately analyzes the coordination problem of multiple permanent magnet synchronous motors. On the one hand, the method proposed by the present invention is simple and easy to realize in engineering, and will not be limited by the number of motors. On the other hand, when some motors exit the system due to failure or other reasons and new motors are re-connected to the system, the method is still valid, and the robustness and anti-interference ability of the system are further enhanced.

Description

technical field [0001] The invention belongs to the field of motor control under the cooperative working condition of multiple motors, and in particular relates to a distributed self-adaptive coordination control method for multiple permanent magnet synchronous motors. Background technique [0002] With the rapid development of society and technology, the control system of a single motor can no longer meet the control requirements of intelligent manufacturing and industrial automation. The collaborative work of multiple motors has been widely used in many fields such as new energy power generation, collaborative cargo transportation, intelligent assembly, robot formation, and drone formation. In addition, since the permanent magnet synchronous motor not only has the characteristics of high torque-to-inertia ratio and high torque-to-mass ratio, but also has a series of advantages such as high efficiency, simple structure, and low manufacturing cost, it is necessary to study e...

AI Technical Summary

Problems solved by technology

[0007] 1. In the existing control structure, the parallel independent control structure is proved not suitable for the coordinated control of multiple motors;

[0008] 2. In the master-slave control structure, the slave motor is greatly affected by the master motor, and the system's anti-interference ability is poor, and as the number of motors increases, the system control structure will become more and more complicated;

[0009] 3. In the deviation coupling control structure, when the number of motors is large, the calculation of synchronization error is more complicated, and the engineering application is greatly restricted;

[0010] 4. Among the existing control algorithms, the PID algorithm has poor control accuracy and anti-interference ability;

[0011] 5. The neural network algorithm is complex in operation and slow in response;

[0012] 5. There is a problem of over-adaptation in sliding mode control;

[0013] 6. Adaptive control has attracted widespread attention because it can effectively adjust the position parameters in the system or controller, but if the global information of the system is required, the amount of calculation will be extremely large;

[0014] In summary, the traditional coordinated control of multiple motors pays more attention to the control performance of a single motor from the micro level, and seldom analyzes the group dynamics behavior of multiple motors from the macro level. Some control structures and control algorithms are limited by the number of motors

Furthermore, when some motors exit due to failure or other reasons and new motors re-enter the system, the existing control methods will be limited

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