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- W4313012783 abstract "In this paper the Fixed Point Iteration-based adaptive control of an underactuated mechanical system is considered. In this arrangement the not controlled variable acts as a parasite dynamics due to a nonlinear coupling disturbs the motion of the controlled one. The system does not contain sensor to measure the uncontrolled variable’s value. Consequently the precise dynamic model cannot be used, being in lack of appropriate information. To tackle this problem the adaptive controller uses a primitive affine model for the observable variable and compensates the consequences of its imprecisions by adaptive deformation. In this paper it is shown by simulations that the parameters of this primitive affine model can be further fine-tuned by Particle Swarm optimization, therefore the quality of control can be improved, too." @default.
- W4313012783 created "2023-01-05" @default.
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- W4313012783 date "2022-07-06" @default.
- W4313012783 modified "2023-10-02" @default.
- W4313012783 title "Tuning of Dynamic Model Parameters for Adaptive Control Using Particle Swarm Optimization" @default.
- W4313012783 doi "https://doi.org/10.1109/iccc202255925.2022.9922801" @default.
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