Balance Adjustment of Power-Line Inspection Robot Using General Type-2 Fractional Order Fuzzy PID Controller
In this study, a general type-2 fractional order fuzzy PID (GT2FO-FPID) controller is proposed to fulfil the balance adjustment of the Power-line Inspection (PLI) robot system. It is a combination of Mamdani general type-2 fuzzy logic controller (GT2-FLC) and fractional PID controller. Since the PLI...
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doaj-f931622cf967470bb34abf8ea803c7862020-11-25T02:38:13ZengMDPI AGSymmetry2073-89942020-03-0112347910.3390/sym12030479sym12030479Balance Adjustment of Power-Line Inspection Robot Using General Type-2 Fractional Order Fuzzy PID ControllerYao Chen0Tao Zhao1Songyi Dian2Xiaodong Zeng3Haipeng Wang4College of Electrical Engineering, Sichuan University, Chengdu 610065, ChinaCollege of Electrical Engineering, Sichuan University, Chengdu 610065, ChinaCollege of Electrical Engineering, Sichuan University, Chengdu 610065, ChinaCollege of Electrical Engineering, Sichuan University, Chengdu 610065, ChinaShandong Luneng Intelligence Technology Co., Ltd., Jinan 250002, ChinaIn this study, a general type-2 fractional order fuzzy PID (GT2FO-FPID) controller is proposed to fulfil the balance adjustment of the Power-line Inspection (PLI) robot system. It is a combination of Mamdani general type-2 fuzzy logic controller (GT2-FLC) and fractional PID controller. Since the PLI robot system is an under-actuated system, it’s necessary to get complete information of the system. However, when all state variables are treated as input to the controller, there is a problem with the rule explosion. Because of this, the information fusion method is adopt to solve the problem and simplify the controller design. At the same time, fractional-order integral-differential operators and input-output scaling factors, which are taken as design variables and optimized by genetic algorithm (GA). To assess the performance of proposed controller based on symmetry criterion, we compared it against existing controllers, i.e., interval type-2 fractional order fuzzy PID (IT2FO-FPID), type-1 fractional order fuzzy PID (T1FO-FPID), and conventional fractional order (FOPID) controllers. Furthermore, to show the anti-inference ability of the proposed controller, three common perturbed process are tested. Finally, simulation results show that the GT2FO-FPID controller outperforms other controllers in the presence of external perturbations on the PLI robot system.https://www.mdpi.com/2073-8994/12/3/479general type-2 fuzzy controllerfractional order controllerinspection robotunder-actuated nonlinear system |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yao Chen Tao Zhao Songyi Dian Xiaodong Zeng Haipeng Wang |
spellingShingle |
Yao Chen Tao Zhao Songyi Dian Xiaodong Zeng Haipeng Wang Balance Adjustment of Power-Line Inspection Robot Using General Type-2 Fractional Order Fuzzy PID Controller Symmetry general type-2 fuzzy controller fractional order controller inspection robot under-actuated nonlinear system |
author_facet |
Yao Chen Tao Zhao Songyi Dian Xiaodong Zeng Haipeng Wang |
author_sort |
Yao Chen |
title |
Balance Adjustment of Power-Line Inspection Robot Using General Type-2 Fractional Order Fuzzy PID Controller |
title_short |
Balance Adjustment of Power-Line Inspection Robot Using General Type-2 Fractional Order Fuzzy PID Controller |
title_full |
Balance Adjustment of Power-Line Inspection Robot Using General Type-2 Fractional Order Fuzzy PID Controller |
title_fullStr |
Balance Adjustment of Power-Line Inspection Robot Using General Type-2 Fractional Order Fuzzy PID Controller |
title_full_unstemmed |
Balance Adjustment of Power-Line Inspection Robot Using General Type-2 Fractional Order Fuzzy PID Controller |
title_sort |
balance adjustment of power-line inspection robot using general type-2 fractional order fuzzy pid controller |
publisher |
MDPI AG |
series |
Symmetry |
issn |
2073-8994 |
publishDate |
2020-03-01 |
description |
In this study, a general type-2 fractional order fuzzy PID (GT2FO-FPID) controller is proposed to fulfil the balance adjustment of the Power-line Inspection (PLI) robot system. It is a combination of Mamdani general type-2 fuzzy logic controller (GT2-FLC) and fractional PID controller. Since the PLI robot system is an under-actuated system, it’s necessary to get complete information of the system. However, when all state variables are treated as input to the controller, there is a problem with the rule explosion. Because of this, the information fusion method is adopt to solve the problem and simplify the controller design. At the same time, fractional-order integral-differential operators and input-output scaling factors, which are taken as design variables and optimized by genetic algorithm (GA). To assess the performance of proposed controller based on symmetry criterion, we compared it against existing controllers, i.e., interval type-2 fractional order fuzzy PID (IT2FO-FPID), type-1 fractional order fuzzy PID (T1FO-FPID), and conventional fractional order (FOPID) controllers. Furthermore, to show the anti-inference ability of the proposed controller, three common perturbed process are tested. Finally, simulation results show that the GT2FO-FPID controller outperforms other controllers in the presence of external perturbations on the PLI robot system. |
topic |
general type-2 fuzzy controller fractional order controller inspection robot under-actuated nonlinear system |
url |
https://www.mdpi.com/2073-8994/12/3/479 |
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