Article
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Proposals for Surmounting Sensor Noises
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Version 1
: Received: 13 November 2022 / Approved: 14 November 2022 / Online: 14 November 2022 (09:27:25 CET)
A peer-reviewed article of this Preprint also exists.
Pittella, A.; Sands, T. Proposals for Surmounting Sensor Noises. Sensors 2023, 23, 3169. Pittella, A.; Sands, T. Proposals for Surmounting Sensor Noises. Sensors 2023, 23, 3169.
Abstract
Classical and optimal control architectures for motion mechanics with fusion of noisy sensors use different algorithms and calculations to perform and control any number of physical demands, to varying degrees of accuracy, precision, and cost. Their performances are tested for the purpose of comparison through the means of a Monte Carlo simulation that simulates how different parameters might vary under noise, representing real-world imperfect sensors. We find that improvements in one figure of merit often come at a cost in the performance in the others, especially depending on the presence of noise in the system sensors. If sensor noise is negligible, open-loop optimal control performs the best. However, in the overpowering presence of sensor noise, using a control law inversion patching filter performs as the best replacement, but has significant computational strain.
Keywords
sensor fusion; sensor noise; optimization; feedback; real-time optimization; velocity-based controller
Subject
Engineering, Mechanical Engineering
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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