Effects of linear filter on stability and performance of human-in-the-loop model reference adaptive control architectures
Date
2017Source Title
Proceedings of the ASME 2017 Dynamic Systems and Control Conference, DSCC 2017
Publisher
ASME
Pages
1 - 10
Language
English
Type
Conference PaperItem Usage Stats
218
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191
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Abstract
Model reference adaptive control (MRAC) can effectively handle various challenges of the real world control problems including exogenous disturbances, system uncertainties, and degraded modes of operations. In human-in-the-loop settings, MRAC may cause unstable system trajectories. Basing on our recent work on the stability of MRAC-human dynamics, here we follow an optimization based computations to design a linear filter and study whether or not this filter inserted between the human model and MRAC could help remove such instabilities, and potentially improve performance. To this end, we present a mathematical approach to study how the error dynamics of MRAC could favorably or detrimentally influence human operator's error dynamics in performing a certain task. An illustrative numerical example concludes the study.
Keywords
Adaptive control systemsAdvanced driver assistance systems
Advanced vehicle control systems
Aerospace applications
Automobile drivers
Bandpass filters
Intelligent robots
Intelligent systems
Linear control systems
Machine design
Mathematical operators
Robotics
Signal filtering and prediction
Wind power
Exogenous disturbances
Human-in-the-loop
Improve performance
Mathematical approach
Modes of operation
Real world control
System uncertainties
Model reference adaptive control
Permalink
http://hdl.handle.net/11693/37569Published Version (Please cite this version)
http://dx.doi.org/10.1115/DSCC2017-5001Collections
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