On-line adaptive fuzzy switching controller for SCARA robot

A. Marwan, Farrukh Nagi, Khairul Salleh Mohamed Sahari, Hanim Salleh, I. Fadi

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This paper presents the design, development and implementation of a new on-line adaptive MIMO switching controller (FSC) for real-time tracking control of an industrial SCARA robot. Two link SCARA robot is a nonlinear plant. The fuzzy control is based on the Takagi-Sugeno's type fuzzy architecture model with on-line self-tuning so that both the desired transient and steady state responses can be achieved at different operation conditions. The online real-time self-tuning is based on the gradient steepest descent method, which tunes the inputs and outputs scaling factors of the proposed fuzzy controller. This controller simplifies the Real-time control implementation and improves the control performance. Real-time controller is implemented in Matlab's xPC Real-time workshop environment. SCARA robot system identification was accomplished by using Auto Regression with external input method (ARX) to determine the discrete time transfer function necessary for the controller design. Comparison between the self-tuned fuzzy switching controller and fixed fuzzy switching controller was made to evaluate the real time tuning's performance. The comparison is based on the tracking ability subjected to large payload. Based on the real time results the performance of fuzzy switching controller with this tuning strategy was found to be superior and it matches favourably to the operating conditions.

Original languageEnglish
Pages (from-to)404-416
Number of pages13
JournalWSEAS Transactions on Systems and Control
Volume6
Issue number11
Publication statusPublished - 01 Nov 2011

Fingerprint

Robot
Robots
Controller
Controllers
Real-time
Self-tuning
Tuning
Gradient Descent Method
Industrial Robot
Steepest Descent Method
Autoregression
Scaling Factor
Transient State
Tracking Control
Steepest descent method
Fuzzy Controller
Fuzzy Control
System Identification
Controller Design
Multiple-input multiple-output (MIMO)

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Control and Optimization

Cite this

@article{8062dbc939e64ca9975903fc02b8db78,
title = "On-line adaptive fuzzy switching controller for SCARA robot",
abstract = "This paper presents the design, development and implementation of a new on-line adaptive MIMO switching controller (FSC) for real-time tracking control of an industrial SCARA robot. Two link SCARA robot is a nonlinear plant. The fuzzy control is based on the Takagi-Sugeno's type fuzzy architecture model with on-line self-tuning so that both the desired transient and steady state responses can be achieved at different operation conditions. The online real-time self-tuning is based on the gradient steepest descent method, which tunes the inputs and outputs scaling factors of the proposed fuzzy controller. This controller simplifies the Real-time control implementation and improves the control performance. Real-time controller is implemented in Matlab's xPC Real-time workshop environment. SCARA robot system identification was accomplished by using Auto Regression with external input method (ARX) to determine the discrete time transfer function necessary for the controller design. Comparison between the self-tuned fuzzy switching controller and fixed fuzzy switching controller was made to evaluate the real time tuning's performance. The comparison is based on the tracking ability subjected to large payload. Based on the real time results the performance of fuzzy switching controller with this tuning strategy was found to be superior and it matches favourably to the operating conditions.",
author = "A. Marwan and Farrukh Nagi and {Mohamed Sahari}, {Khairul Salleh} and Hanim Salleh and I. Fadi",
year = "2011",
month = "11",
day = "1",
language = "English",
volume = "6",
pages = "404--416",
journal = "WSEAS Transactions on Systems and Control",
issn = "1991-8763",
publisher = "World Scientific and Engineering Academy and Society",
number = "11",

}

On-line adaptive fuzzy switching controller for SCARA robot. / Marwan, A.; Nagi, Farrukh; Mohamed Sahari, Khairul Salleh; Salleh, Hanim; Fadi, I.

In: WSEAS Transactions on Systems and Control, Vol. 6, No. 11, 01.11.2011, p. 404-416.

Research output: Contribution to journalArticle

TY - JOUR

T1 - On-line adaptive fuzzy switching controller for SCARA robot

AU - Marwan, A.

AU - Nagi, Farrukh

AU - Mohamed Sahari, Khairul Salleh

AU - Salleh, Hanim

AU - Fadi, I.

PY - 2011/11/1

Y1 - 2011/11/1

N2 - This paper presents the design, development and implementation of a new on-line adaptive MIMO switching controller (FSC) for real-time tracking control of an industrial SCARA robot. Two link SCARA robot is a nonlinear plant. The fuzzy control is based on the Takagi-Sugeno's type fuzzy architecture model with on-line self-tuning so that both the desired transient and steady state responses can be achieved at different operation conditions. The online real-time self-tuning is based on the gradient steepest descent method, which tunes the inputs and outputs scaling factors of the proposed fuzzy controller. This controller simplifies the Real-time control implementation and improves the control performance. Real-time controller is implemented in Matlab's xPC Real-time workshop environment. SCARA robot system identification was accomplished by using Auto Regression with external input method (ARX) to determine the discrete time transfer function necessary for the controller design. Comparison between the self-tuned fuzzy switching controller and fixed fuzzy switching controller was made to evaluate the real time tuning's performance. The comparison is based on the tracking ability subjected to large payload. Based on the real time results the performance of fuzzy switching controller with this tuning strategy was found to be superior and it matches favourably to the operating conditions.

AB - This paper presents the design, development and implementation of a new on-line adaptive MIMO switching controller (FSC) for real-time tracking control of an industrial SCARA robot. Two link SCARA robot is a nonlinear plant. The fuzzy control is based on the Takagi-Sugeno's type fuzzy architecture model with on-line self-tuning so that both the desired transient and steady state responses can be achieved at different operation conditions. The online real-time self-tuning is based on the gradient steepest descent method, which tunes the inputs and outputs scaling factors of the proposed fuzzy controller. This controller simplifies the Real-time control implementation and improves the control performance. Real-time controller is implemented in Matlab's xPC Real-time workshop environment. SCARA robot system identification was accomplished by using Auto Regression with external input method (ARX) to determine the discrete time transfer function necessary for the controller design. Comparison between the self-tuned fuzzy switching controller and fixed fuzzy switching controller was made to evaluate the real time tuning's performance. The comparison is based on the tracking ability subjected to large payload. Based on the real time results the performance of fuzzy switching controller with this tuning strategy was found to be superior and it matches favourably to the operating conditions.

UR - http://www.scopus.com/inward/record.url?scp=82555161615&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=82555161615&partnerID=8YFLogxK

M3 - Article

VL - 6

SP - 404

EP - 416

JO - WSEAS Transactions on Systems and Control

JF - WSEAS Transactions on Systems and Control

SN - 1991-8763

IS - 11

ER -