Effects of linear filter on stability and performance of human-in-the-loop model reference adaptive control architectures
Demir, Didem Fatma
Proceedings of the ASME 2017 Dynamic Systems and Control Conference, DSCC 2017
1 - 10
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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.
KeywordsAdaptive control systems
Advanced driver assistance systems
Advanced vehicle control systems
Linear control systems
Signal filtering and prediction
Modes of operation
Real world control
Model reference adaptive control
Published Version (Please cite this version)http://dx.doi.org/10.1115/DSCC2017-5001
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