Model -Free Adaptive Control With Fuzzy Component for Tower Crane Systems

The objective of the current paper is to improve the performance of data-driven Model-Free Adaptive Control (MFAC) by adding a Proportional-Derivative Takagi-Sugeno fuzzy controller (PDTSFC) component. This MFAC improvement is called MFAC-Proportional-Derivative Takagi-Sugeno Fuzzy Controller (MFAC-...

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Bibliographic Details
Main Authors: Roman, Raul-Cristian, Precup, Radu-Emil, Petriu, Emil M., Hedrea, Elena-Lorena, Bojan-Dragos, Claudia-Adina, Radac, Mircea-Bogdan
Format: Conference Proceeding
Language:English
Subjects:
Automation
Cranes
data-driven
fuzzy control
Informatics
Mathematical model
PD control
Poles and towers
simulation results
Takagi-Sugeno model
tower crane system
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Summary:The objective of the current paper is to improve the performance of data-driven Model-Free Adaptive Control (MFAC) by adding a Proportional-Derivative Takagi-Sugeno fuzzy controller (PDTSFC) component. This MFAC improvement is called MFAC-Proportional-Derivative Takagi-Sugeno Fuzzy Controller (MFAC-PDTSFC). MFAC-PDTSFC is applied to a Multi Input-Multi Output control structure of a mathematical model that describes the behavior of a nonlinear tower crane system (TCS) laboratory equipment. The MFAC-PDTSFC parameters are tuned in a model-based manner using metaheuristic Grey Wolf optimizer algorithm. The performances of the new MFAC-PDTSFC are compared with those of MFAC and Proportional-Derivative Takagi-Sugeno Fuzzy Controller (PDTSFC).
ISSN:2577-1655
DOI:10.1109/SMC.2019.8914376