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A Novel Self-Organizing PID Approach for Controlling Mobile Robot Locomotion

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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A Novel Self-Organizing PID Approach for Controlling Mobile Robot Locomotion. / Gu, Xiaowei; Khan, Muhammad; Angelov, Plamen et al.
2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2020. p. 1-10.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Gu, X, Khan, M, Angelov, P, Tiwary, B, Shafipour Yourdshahi, E & Yang, Z 2020, A Novel Self-Organizing PID Approach for Controlling Mobile Robot Locomotion. in 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, pp. 1-10. https://doi.org/10.1109/FUZZ48607.2020.9177557

APA

Gu, X., Khan, M., Angelov, P., Tiwary, B., Shafipour Yourdshahi, E., & Yang, Z. (2020). A Novel Self-Organizing PID Approach for Controlling Mobile Robot Locomotion. In 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (pp. 1-10). IEEE. https://doi.org/10.1109/FUZZ48607.2020.9177557

Vancouver

Gu X, Khan M, Angelov P, Tiwary B, Shafipour Yourdshahi E, Yang Z. A Novel Self-Organizing PID Approach for Controlling Mobile Robot Locomotion. In 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE. 2020. p. 1-10 doi: 10.1109/FUZZ48607.2020.9177557

Author

Gu, Xiaowei ; Khan, Muhammad ; Angelov, Plamen et al. / A Novel Self-Organizing PID Approach for Controlling Mobile Robot Locomotion. 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2020. pp. 1-10

Bibtex

@inproceedings{2bcacf4061c2490ea728f2c552e28963,
title = "A Novel Self-Organizing PID Approach for Controlling Mobile Robot Locomotion",
abstract = "A novel self-organizing fuzzy proportional-integral-derivative (SOF-PID) control system is proposed in this paper. The proposed system consists of a pair of control and reference models, both of which are implemented by a first-order autonomous learning multiple model (ALMMo) neuro-fuzzy system. The SOF-PID controller self-organizes and self-updates the structures and meta-parameters of both the control and reference models during the control process {"}on the fly{"}. This gives the SOF-PID control system the capability of quickly adapting to entirely new operating environments without a full re-training. Moreover, the SOF-PID control system is free from user- and problem-specific parameters and is entirely data-driven. Simulations and real-world experiments with mobile robots demonstrate the effectiveness and validity of the proposed SOF-PID control system.",
author = "Xiaowei Gu and Muhammad Khan and Plamen Angelov and Bikash Tiwary and {Shafipour Yourdshahi}, Elnaz and Zhaoxu Yang",
note = "{\textcopyright}2020 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. ",
year = "2020",
month = aug,
day = "26",
doi = "10.1109/FUZZ48607.2020.9177557",
language = "English",
isbn = "9781728169330",
pages = "1--10",
booktitle = "2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - A Novel Self-Organizing PID Approach for Controlling Mobile Robot Locomotion

AU - Gu, Xiaowei

AU - Khan, Muhammad

AU - Angelov, Plamen

AU - Tiwary, Bikash

AU - Shafipour Yourdshahi, Elnaz

AU - Yang, Zhaoxu

N1 - ©2020 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

PY - 2020/8/26

Y1 - 2020/8/26

N2 - A novel self-organizing fuzzy proportional-integral-derivative (SOF-PID) control system is proposed in this paper. The proposed system consists of a pair of control and reference models, both of which are implemented by a first-order autonomous learning multiple model (ALMMo) neuro-fuzzy system. The SOF-PID controller self-organizes and self-updates the structures and meta-parameters of both the control and reference models during the control process "on the fly". This gives the SOF-PID control system the capability of quickly adapting to entirely new operating environments without a full re-training. Moreover, the SOF-PID control system is free from user- and problem-specific parameters and is entirely data-driven. Simulations and real-world experiments with mobile robots demonstrate the effectiveness and validity of the proposed SOF-PID control system.

AB - A novel self-organizing fuzzy proportional-integral-derivative (SOF-PID) control system is proposed in this paper. The proposed system consists of a pair of control and reference models, both of which are implemented by a first-order autonomous learning multiple model (ALMMo) neuro-fuzzy system. The SOF-PID controller self-organizes and self-updates the structures and meta-parameters of both the control and reference models during the control process "on the fly". This gives the SOF-PID control system the capability of quickly adapting to entirely new operating environments without a full re-training. Moreover, the SOF-PID control system is free from user- and problem-specific parameters and is entirely data-driven. Simulations and real-world experiments with mobile robots demonstrate the effectiveness and validity of the proposed SOF-PID control system.

U2 - 10.1109/FUZZ48607.2020.9177557

DO - 10.1109/FUZZ48607.2020.9177557

M3 - Conference contribution/Paper

SN - 9781728169330

SP - 1

EP - 10

BT - 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

PB - IEEE

ER -