Design of Improved Linear Active Disturbance Rejection Control for Non-Minimum Phase Systems

Non-minimum phase systems, which are common in power generation due to their inherent instability, pose significant control challenges. To address this, an Improved Linear Active Disturbance Rejection Control (ILADRC) is proposed. This method involves decomposing the system model into minimum phase and non-minimum phase components, designing a feedforward compensator based on the minimum phase component, and developing a non-minimum phase Smith predictor compensator for the non-minimum phase part. Additionally, a rule for simplified parameter tuning of the ILADRC is introduced. The effectiveness of the proposed ILADRC was demonstrated through experiments using steam valve regulation in a turbine as a case study, compared with PID and LADRC. The results show that the proposed ILADRC outperforms existing methods in set-point tracking and disturbance rejection. Monte Carlo robustness tests further confirm the robustness advantage of the ILADRC, highlighting its significant potential for practical engineering applications.

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Published
2024-12-13
DOI
https://doi.org/10.1109/icpes63746.2024.10856640
Primary Topic
Iterative Learning Control Systems
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article
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article

Design of Improved Linear Active Disturbance Rejection Control for Non-Minimum Phase Systems

Wu Maoqian, Liu We, Xiang Lin, Dong Lijiang et al.
Iterative Learning Control Systems
article

Design of Improved Linear Active Disturbance Rejection Control for Non-Minimum Phase Systems

Wu Maoqian, Liu We, Xiang Lin, Dong Lijiang, Qian Baiyun, Yang Chaojie
article en

Abstract

Non-minimum phase systems, which are common in power generation due to their inherent instability, pose significant control challenges. To address this, an Improved Linear Active Disturbance Rejection Control (ILADRC) is proposed. This method involves decomposing the system model into minimum phase and non-minimum phase components, designing a feedforward compensator based on the minimum phase component, and developing a non-minimum phase Smith predictor compensator for the non-minimum phase part. Additionally, a rule for simplified parameter tuning of the ILADRC is introduced. The effectiveness of the proposed ILADRC was demonstrated through experiments using steam valve regulation in a turbine as a case study, compared with PID and LADRC. The results show that the proposed ILADRC outperforms existing methods in set-point tracking and disturbance rejection. Monte Carlo robustness tests further confirm the robustness advantage of the ILADRC, highlighting its significant potential for practical engineering applications.

Electric Power Research Institute (US), North China Electric Power University (CN), Xinjiang New Energy Research Institute (China) (CN)
Climate action
Openalex Percentile: Top 68%
Iterative Learning Control Systems
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