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http://dx.doi.org/10.5302/J.ICROS.2014.14.0046

Sensing Parameter Selection Strategy for Ultra-low-power Micro-servosystem Identification  

Hahn, Bongsu (Department of Applied Robotics, Kyungil University)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.20, no.8, 2014 , pp. 849-853 More about this Journal
Abstract
In micro-scale electromechanical systems, the power to perform accurate position sensing often greatly exceeds the power needed to generate motion. This paper explores the implications of sampling rate and amplifier noise density selection on the performance of a system identification algorithm using a capacitive sensing circuit. Specific performance objectives are to minimize or limit convergence rate and power consumption to identify the dynamics of a rotary micro-stage. A rearrangement of the conventional recursive least-squares identification algorithm is performed to make operating cost an explicit function of sensor design parameters. It is observed that there is a strong dependence of convergence rate and error on the sampling rate, while energy dependence is driven by error that may be tolerated in the final identified parameters.
Keywords
recursive least square; sample rate; identification; ultra-low-power systems;
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