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Predictor-based disturbance rejection control for sampled systems with input delay
journal contribution
posted on 2017-12-08, 13:34 authored by Tao Liu, Shoulin Hao, Dewei Li, Wen-Hua ChenWen-Hua Chen, Qing-Guo WangTo cope with input delay involved with many industrial system operations, a predictor-based disturbance rejection control (PDRC) scheme is proposed in discrete-time domain for sampling implementation, which can be generally applied for open-loop stable, integrating and unstable processes.
An extended state observer (ESO) is introduced to estimate not only the deterministic system state but also the generalized disturbance composed of system uncertainties and external disturbance, based on a filtered Smith predictor to estimate the delay-free output response. Correspondingly, by specifying the desired poles of ESO and the closed-loop control system, the ESO gain vector and the PDRC controller are analytically derived. A notable merit is that there is a single tuning parameter in the proposed ESO, output predictor, and the PDRC controller, which can be monotonically tuned to achieve a good trade-off between
the prediction (or control) performance and its robustness. A
sufficient robust stability condition of the closed-loop system is established in terms of linear matrix inequality (LMI). An illustrative example from the literature along with an application to the temperature control system for a crystallization reactor is used to demonstrate the effectiveness and advantage of the proposed control method.
Funding
This work is supported in part by the NSF China Grants 61633006 and 61473054, and the National Thousand Talents Program of China.
History
School
- Aeronautical, Automotive, Chemical and Materials Engineering
Department
- Aeronautical and Automotive Engineering
Published in
IEEE Transactions on Control Systems TechnologyCitation
LIU, T. ... et al, 2017. Predictor-based disturbance rejection control for sampled systems with input delay. IEEE Transactions on Control Systems Technology, 27 (2), pp.772-780.Publisher
© IEEEVersion
- AM (Accepted Manuscript)
Acceptance date
2017-11-26Publication date
2017Notes
© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.ISSN
1063-6536Publisher version
Language
- en