Motor controller based on parameter self-tuning and control method thereof

Abstract

The invention discloses a motor controller based on parameter self-tuning and a control method thereof, and relates to the field of motor control system devices. According to the motor controller based on parameter self-tuning and the control method thereof, the control parameters of a PID controller are self-tuned by identifying the rotational inertia of a system ahead of time and converting a controlled system into a first-order inertia link and a second-order inertia link. Thus, the motor controller and the control method have higher engineering practicability. The controller has good motor control performance, and can self-tune the control parameters. Thus, the optimal parameters of a motor control system can be obtained, and the motor control system can adapt to more complex conditions and meet the requirement of users for high performance index. The motor controller and the control method are of great theoretical research value and engineering practical significance. The motor controller and the control method can be widely used in intelligent wheelchair control, unmanned lawn mowers, industrial automation, air defense, and other industries.

Description

technical field [0001] The invention relates to the field of motor control system devices, in particular to a motor controller based on a parameter self-tuning and a control method thereof. Background technique [0002] With the rapid development of industries such as national defense, aviation, intelligent industry, and industrial control, the demand for motor control systems is also increasing. At the same time, higher requirements are put forward for the motor control system. excellent performance. Therefore, the development of a high-performance motor drive system with excellent adaptability has very significant economic and social benefits. [0003] At present, the parameter setting work of most types of controllers is mainly done manually. It is time-consuming and laborious to adjust the controller parameters multiple times by observing the law of the system’s operating state under different parameters, and the effect of parameter setting is not good. Operators have ...

AI Technical Summary

Problems solved by technology

[0003] At present, the parameter setting work of most types of controllers is mainly done manually. It is time-consuming and laborious to adjust the controller parameters multiple times by observing the law of the system’s operating state under different parameters, and the effect of parameter setting is not good. Operators have higher requirements

If the result of parameter tuning is not satisfactory, the system will be put into use, which will greatly affect the performance of the system, and even cause the system to be unstable.

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