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Design of an Automatically Tuned Fuzzy Controller for a Truck and Multitrailer System
Author(s) -
Tao Ren
Publication year - 2013
Publication title -
advances in mechanical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 40
eISSN - 1687-8140
pISSN - 1687-8132
DOI - 10.1155/2013/549838
Subject(s) - controller (irrigation) , truck , particle swarm optimization , fuzzy logic , control engineering , control theory (sociology) , computer science , fuzzy control system , position (finance) , trailer , task (project management) , engineering , control (management) , automotive engineering , artificial intelligence , algorithm , systems engineering , finance , economics , agronomy , biology
The use of a truck and multitrailer system is advantageous because of its ability to transport heavy and large parts with a single powered vehicle. On the other hand, when the system is deployed in an autonomous and unmanned scenario, it remains a challenging task to design a drive controller. Since the drive is only applied to the truck and motivated by successful cases of human expert drivers, a fuzzy controller is developed to generate speed and turn rate commands in order to steer the multi-trailer system to reach the target position with minimum position error. Furthermore, in order to make the controller design efficient and effective, the parameters in the fuzzy controller including the membership functions and rules are automatically tuned using the implementation of efficient particle swarm optimization algorithm instead of relying solely on human expert knowledge. Near-optimal parameters are then derived and adopted in the controller, and drive commands are then generated. The performance of the truck-and-multi-trailer system under fuzzy control is verified through simulation studies, and satisfactory results are obtained

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