TNNLS-2021-P-17678.pdf (23.04 MB)
Sampled-data output feedback control for nonlinear uncertain systems using predictor-based continuous-discrete observer
journal contribution
posted on 2022-11-11, 14:56 authored by Jiankun Sun, Jun YangJun Yang, Zhigang Zeng, Huiming WangIn this article, we investigate the problem of sampled-data robust output feedback control for a class of nonlinear uncertain systems with time-varying disturbance and measurement delay based on continuous-discrete observer. An augmented system that includes the nonlinear uncertain system and disturbance model is first found, and by using the delayed sampled-data output, we then propose a novel predictor-based continuous-discrete observer to estimate the unknown state and disturbance information. After that, in order to attenuate the undesirable influences of nonlinear uncertainties and disturbance, a sampled-data robust output feedback controller is developed based on disturbance/uncertainty estimation and attenuation technique. It shows that under the proposed control method, the states of overall hybrid nonlinear system can converge to a bounded region centered at the origin. The main benefit of the proposed control method is that in the presence of measurement delay, the influences of time-varying disturbance and nonlinear uncertainties can be effectively attenuated with the help of feedback domination method and prediction technique. Finally, the effectiveness of the proposed control method is demonstrated via the simulation results of a numerical example and a practical example.
Funding
National Natural Science Foundation of China under Grants U1913602 and 62003144
The generation and evolution of human-like emotion based on memristive and its application in emotional robots
National Natural Science Foundation of China
Find out more...Technology Innovation Project of Hubei Province of China under Grant 2019AEA171
National Postdoctoral Program for Innovative Talents of China under Grant BX20200140
Postdoctoral Science Foundation of China under Grant 2020M682415
Natural Science Foundation Project of Chongqing, PR China under Grant cstc2021jcyj-msxmX0142
History
School
- Aeronautical, Automotive, Chemical and Materials Engineering
Department
- Aeronautical and Automotive Engineering
Published in
IEEE Transactions on Neural Networks and Learning SystemsVolume
34Issue
11Pages
9223 - 9233Publisher
Institute of Electrical and Electronics Engineers (IEEE)Version
- AM (Accepted Manuscript)
Rights holder
© IEEEPublisher statement
© 2022 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.Acceptance date
2022-03-02Publication date
2022-03-18Copyright date
2022ISSN
2162-237XeISSN
2162-2388Publisher version
Language
- en
Depositor
Dr Jun Yang. Deposit date: 10 November 2022Usage metrics
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