A novel self-organizing PID approach for controlling mobile robot locomotion
A novel self-organizing PID approach for controlling mobile robot locomotion
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.
Gu, Xiaowei
39d21b7d-4393-42d6-8060-bb1b05a3bd08
Khan, Muhammad
737adabc-59d4-46b5-81ed-1185ac90f83b
Angelov, Plamen
30ed50c8-95c0-44c8-aa44-bef2a25e2fb5
Tiwary, Bikash
d366f2f2-abc0-4673-958f-0598f763aa99
Shafipour Yourdshahi, Elnaz
a2e1dea9-d3c0-4288-afdc-197df65f2556
Yang, Zhaoxu
a940f13a-01b6-45f9-8c7e-b94ff46ceebd
25 August 2020
Gu, Xiaowei
39d21b7d-4393-42d6-8060-bb1b05a3bd08
Khan, Muhammad
737adabc-59d4-46b5-81ed-1185ac90f83b
Angelov, Plamen
30ed50c8-95c0-44c8-aa44-bef2a25e2fb5
Tiwary, Bikash
d366f2f2-abc0-4673-958f-0598f763aa99
Shafipour Yourdshahi, Elnaz
a2e1dea9-d3c0-4288-afdc-197df65f2556
Yang, Zhaoxu
a940f13a-01b6-45f9-8c7e-b94ff46ceebd
Gu, Xiaowei, Khan, Muhammad, Angelov, Plamen, Tiwary, Bikash, Shafipour Yourdshahi, Elnaz and Yang, Zhaoxu
(2020)
A novel self-organizing PID approach for controlling mobile robot locomotion.
In,
2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).
(doi:10.1109/FUZZ48607.2020.9177557).
Record type:
Book Section
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.
Text
PID6416689
- Accepted Manuscript
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Published date: 25 August 2020
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Local EPrints ID: 469613
URI: http://eprints.soton.ac.uk/id/eprint/469613
PURE UUID: a5b7dfdd-d781-4b2a-a577-4d88f8652818
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Date deposited: 21 Sep 2022 16:38
Last modified: 16 Mar 2024 22:22
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Contributors
Author:
Xiaowei Gu
Author:
Muhammad Khan
Author:
Plamen Angelov
Author:
Bikash Tiwary
Author:
Elnaz Shafipour Yourdshahi
Author:
Zhaoxu Yang
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