{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T17:13:44Z","timestamp":1763226824438,"version":"build-2065373602"},"reference-count":40,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2020,3,19]],"date-time":"2020-03-19T00:00:00Z","timestamp":1584576000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"State gird headquarters Science and Technology Projects of China","award":["5500-201916260A-0-0-00"],"award-info":[{"award-number":["5500-201916260A-0-0-00"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>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\u2019s 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.<\/jats:p>","DOI":"10.3390\/sym12030479","type":"journal-article","created":{"date-parts":[[2020,3,20]],"date-time":"2020-03-20T07:29:07Z","timestamp":1584689347000},"page":"479","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Balance Adjustment of Power-Line Inspection Robot Using General Type-2 Fractional Order Fuzzy PID Controller"],"prefix":"10.3390","volume":"12","author":[{"given":"Yao","family":"Chen","sequence":"first","affiliation":[{"name":"College of Electrical Engineering, Sichuan University, Chengdu 610065, China"}]},{"given":"Tao","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Electrical Engineering, Sichuan University, Chengdu 610065, China"}]},{"given":"Songyi","family":"Dian","sequence":"additional","affiliation":[{"name":"College of Electrical Engineering, Sichuan University, Chengdu 610065, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2103-750X","authenticated-orcid":false,"given":"Xiaodong","family":"Zeng","sequence":"additional","affiliation":[{"name":"College of Electrical Engineering, Sichuan University, Chengdu 610065, China"}]},{"given":"Haipeng","family":"Wang","sequence":"additional","affiliation":[{"name":"Shandong Luneng Intelligence Technology Co., Ltd., Jinan 250002, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Caponetto, R. 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