Design method for linear active-disturbance-rejection controller based on prediction tracking differentiator

Abstract

The invention relates to a design method for a linear active-disturbance-rejection controller based on a prediction tracking differentiator, and the method comprises the following steps: a, designingthe prediction tracking differentiator, and performing the filtering of an obtained state signal through the prediction tracking differentiator to obtain a filter value; b, obtaining an extension state of the system through an extension state observer based on the filter value; c, correcting a PD control law through the extension state to obtain the linear active-disturbance-rejection controller.The method provided by the invention can inhibit the impact on the closed-loop characteristics of a system from the noise pollution, can effectively inhibit the phase delay phenomenon caused by the filtering, solves a problem of noise pollution amplification caused by a high-gain observer, and improves the robustness of a controller. The method improves the robustness of the active-disturbance-rejection controller to the high-frequency noise, and has the engineering practicality.

Description

technical field [0001] The invention relates to a design method of a linear active disturbance rejection controller based on a predictive tracking differentiator. Background technique [0002] Since the birth of control theory, it has experienced the development of classical control theory, modern control theory and intelligent control, and established a very rich theoretical system. But except for a few model predictive control, adaptive control and fuzzy control, other modern control algorithms are difficult to be effectively applied in engineering practice. Although the PID control method is simple and widely used, its control performance is often unsatisfactory. In this context, the ADRC technology inherits and develops the advantages of PID control, learns from and absorbs the advanced achievements of modern control theory, does not rely on the precise model of the object, and can effectively suppress various disturbances, and has strong robustness. sex. [0003] The...

AI Technical Summary

Problems solved by technology

This conservative design actually sacrifices the convergence speed and estimation ability of ESO, and weakens the anti-disturbance ability of the ADRC controller.

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