Disturbance prediction based active disturbance rejection control approach
Chongling Li, Tao Cai, Zeyu Han
Abstract
Chongling Li, Tao Cai, Zeyu Han
Abstract
Disturbance widely exists in control system. Active disturbance rejection control (ADRC) has been proved to be an efficient way to deal with disturbance and achieves great success in practice. The most important part of ADRC is extended state observer (ESO), which estimates the states of system and total disturbance. ESO regards internal disturbance and external disturbance as a total disturbance, estimates it and eliminates it in the control. The faster ESO estimates total disturbance, the more quickly controller eliminates it. This paper focuses on the discrete linear extended state observer (DLESO), and presents discrete predictive linear extended state observer (DPLESO). Stability and performances are analyzed. Simulation result shows that DPLESO has better performances for disturbance rejection than DLESO.
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Disturbance widely exists in control system. Active disturbance rejection control (ADRC) has been proved to be an efficient way to deal with disturbance and achieves great success in practice. The most important part of ADRC is extended state observer (ESO), which estimates the states of system and total disturbance. ESO regards internal disturbance and external disturbance as a total disturbance, estimates it and eliminates it in the control. The faster ESO estimates total disturbance, the more quickly controller eliminates it. This paper focuses on the discrete linear extended state observer (DLESO), and presents discrete predictive linear extended state observer (DPLESO). Stability and performances are analyzed. Simulation result shows that DPLESO has better performances for disturbance rejection than DLESO.
Key concepts: Disturbance (geology), Active disturbance rejection control, Control theory (sociology), State observer, Computer science, Controller (irrigation), Stability (learning theory), Control engineering