Parameter tuning method for fractional-order PID controller

Abstract

The invention discloses a parameter tuning method for a fractional-order PID controller, and the method comprises the following steps of calculating an integration order lambda and a differential order mu of a model of the fractional-order PID controller based on a neural network model; and calculating a proportional gain Kp, an integral gain Ki and a differential gain Kd of the model of the fractional-order PID controller by using a horizontal phase criterion based on the obtained integration order lambda and the differential order mu of the model of the fractional-order PID controller. The method provided by the invention first calculates the integration order lambda and the differential order mu of the fractional-order PID controller based on the neural network model, and then calculates the proportional gain Kp, the integral gain Ki and the differential gain Kd of the model of the fractional-order PID controller by using the horizontal phase criterion based on the integration orderlambda and the differential order mu obtained based on the neural network model, which can achieve the best dynamic response performance while ensuring good robustness of the PID controller, and simplify the entire calculation process.

Description

technical field [0001] The invention relates to the technical field of PID automatic control, in particular to a parameter setting method of a fractional order PID controller. Background technique [0002] At present, the traditional feedback control method based on output error is widely used in the servo system, and the controller used is mainly the traditional PID controller. The traditional PID controller model is shown below, where K p is the proportional gain, K i is the integral gain, K d is the differential gain. [0003] The traditional PID controller has the advantages of simple structure and easy implementation, but it is prone to problems such as excessive overshoot and long adjustment time for systems with model uncertainty, and cannot meet the performance index requirements of high-performance motion control systems. Therefore, it is improved and extended to a fractional-order PID controller, and the fractional-order PID controller model is as follows, ...

AI Technical Summary

Problems solved by technology

However, the frequency domain design method cannot guarantee the optimal dynamic response performance of the control system, and the time domain optimization algorithm cannot guarantee the system has good stability and robustness to gain disturbance. A large number of numerical calculations are not conducive to practical applications

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