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

Xiaowei Gu; Muhammad Aurangzeb Khan; Plamen Parvanov Angelov; Bikash Tiwary; Elnaz Shafipour Yourdshahi; Zhaoxu Yang

doi:10.1109/FUZZ48607.2020.9177557

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

Xiaowei Gu, Muhammad Aurangzeb Khan, Plamen Parvanov Angelov, Bikash Tiwary, Elnaz Shafipour Yourdshahi, Zhaoxu Yang

FBMH Platform Sciences, Enabling Technologies & Infrastructure

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Publisher	IEEE
Number of pages	10
ISBN (Electronic)	9781728169323
ISBN (Print)	9781728169330
DOIs	https://doi.org/10.1109/FUZZ48607.2020.9177557
Publication status	Published - 26 Aug 2020

Keywords

ALMMo neuro fuzzy system
PID controller
self-organizing system

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10.1109/FUZZ48607.2020.9177557

Cite this

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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.",

keywords = "ALMMo neuro fuzzy system, PID controller, self-organizing system",

author = "Xiaowei Gu and Khan, {Muhammad Aurangzeb} and Angelov, {Plamen Parvanov} and Bikash Tiwary and Yourdshahi, {Elnaz Shafipour} and Zhaoxu Yang",

year = "2020",

month = aug,

day = "26",

doi = "10.1109/FUZZ48607.2020.9177557",

language = "English",

isbn = "9781728169330",

booktitle = "2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)",

publisher = "IEEE",

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AU - Gu, Xiaowei

AU - Khan, Muhammad Aurangzeb

AU - Angelov, Plamen Parvanov

AU - Tiwary, Bikash

AU - Yourdshahi, Elnaz Shafipour

AU - Yang, Zhaoxu

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.

KW - ALMMo neuro fuzzy system

KW - PID controller

KW - self-organizing system

U2 - 10.1109/FUZZ48607.2020.9177557

DO - 10.1109/FUZZ48607.2020.9177557

M3 - Conference contribution

SN - 9781728169330

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

PB - IEEE

ER -

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

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Keywords

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