NDLI: A model free automatic tuning method for a restricted structured controller by using Simultaneous Perturbation Stochastic Approximation (SPSA)

Content Provider	IEEE Xplore Digital Library
Author	QingHui Yuan
Copyright Year	2008
Description	Author affiliation: Eaton Corp. Innovation Center, Eden Prairie, MN (QingHui Yuan)
Abstract	A model free auto tuning algorithm is developed by using simultaneous perturbation stochastic approximation (SPSA). For such a method, plant models are not required. A set of closed loop experiments are conducted to generate data for an online optimization procedure. The optimum of the parameters of the restricted structured controllers will be found via SPSA algorithm. Compared to the conventional gradient approximation methods, SPSA only needs the small number of measurement of the cost function. It will be beneficial to application with high dimensional parameters. In the paper, a cost function is formulated to directly reflect the control performances widely used in industry, like overshoot, settling time and integral of absolute error. Therefore, the proposed auto tuning method will naturally lead to the desired closed loop performance. A case study of auto tuning of spool position control in a twin spool two stage valve is conducted. Both simulation and experimental study in TI C2000 target demonstrate effectiveness of the algorithm.
Starting Page	1539
Ending Page	1545
File Size	1117005
Page Count	7
File Format	PDF
ISBN	9781424420780
ISSN	07431619
DOI	10.1109/ACC.2008.4586710
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-11
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	American Automatic Control Council(AACC)
Subject Keyword	Automatic control Stochastic processes Cost function Open loop systems Data mining Approximation algorithms Three-term control Tuning Frequency domain analysis Optimization methods
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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