2023
DOI: 10.1177/09544062231151799
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A multi-objective optimization method based on NSGA-II algorithm and entropy weighted TOPSIS for fuzzy active seat suspension of articulated truck semi-trailer

Abstract: This paper aims to optimize a fuzzy logic controller (FLC) active seat suspension applied to an articulated truck semi-trailer seat to improve ride comfort considering the energy consumption of the controller. The proposed truck model is a linear truck with 13 degree-of-freedom (DOF). Two objective functions are defined seat root mean square (RMS) acceleration related to ride comfort and controller RMS force pertaining to the energy consumption of the controller. The Pareto Front is obtained for these two obje… Show more

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Cited by 2 publications
(2 citation statements)
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References 36 publications
(58 reference statements)
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“…Ref. [14] proposed to optimize the fuzzy logic controller (FLC) active seat suspension applied to articulated truck semi-trailer seats by using the NSGA-II algorithm, and the two objective functions optimized are seat vertical acceleration and controller control force to improve the seating comfort. Ref.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Ref. [14] proposed to optimize the fuzzy logic controller (FLC) active seat suspension applied to articulated truck semi-trailer seats by using the NSGA-II algorithm, and the two objective functions optimized are seat vertical acceleration and controller control force to improve the seating comfort. Ref.…”
Section: Introductionmentioning
confidence: 99%
“…The suspension model established by [13][14][15] is mainly a relatively simple 1/4 suspension model; the 1/4 suspension model can only consider the suspension performance indicators at a single axle, and it is difficult to comprehensively evaluate the performance of the whole vehicle, whereas the full vehicle model can take into account the force and movement of the vertical, pitch, roll and other degrees of freedom during the driving process of the car, optimize more indicators, evaluate the vehicle more comprehensively, and be more conducive to the study of the smoothness of the car. Secondly, because fractional order PI λ D µ control has higher design freedom, the design of fractional order PI λ D µ controller is more flexible than integer order PID controller [16,17].…”
Section: Introductionmentioning
confidence: 99%