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Gradient approximations in iterative feedback tuning for multivariable processes
KTH, Superseded Departments, Signals, Sensors and Systems. (Reglerteknik)
KTH, Superseded Departments, Signals, Sensors and Systems. (Reglerteknik)ORCID iD: 0000-0002-9368-3079
2004 (English)In: International journal of adaptive control and signal processing (Print), ISSN 0890-6327, E-ISSN 1099-1115, Vol. 18, no 8, 665-681 p.Article in journal (Refereed) Published
Abstract [en]

Iterative feedback tuning (IFT) is a model free control tuning method using closed-loop experiments. For single-input single-output (SISO) systems only 2 or 3, depending on the controller structure, closed-loop experiments are required. However for multivariable systems the number of experiments increases to be proportional to the dimension of the controller. In this contribution several methods are proposed to reduce the experimental time by approximating the gradient of the cost function. One of these methods uses the same technique of shifting operators as is used in IFT for SISO systems. This method is further analysed and sufficient conditions for local convergence are derived. It is shown that even if there are commutation errors due to the approximation method, the numerical optimization may still converge to the true optimum.

Place, publisher, year, edition, pages
2004. Vol. 18, no 8, 665-681 p.
Keyword [en]
adaptive control, controller tuning, multivariable systems, optimization
National Category
Control Engineering
Research subject
SRA - ICT
Identifiers
URN: urn:nbn:se:kth:diva-23846DOI: 10.1002/acs.826ISI: 000224791900005Scopus ID: 2-s2.0-6344256926OAI: oai:DiVA.org:kth-23846DiVA: diva2:342545
Note

QC 20100525 QC 20110922 QC 20150724

Available from: 2010-08-10 Created: 2010-08-10 Last updated: 2017-12-12Bibliographically approved

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Hjalmarsson, Håkan

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Output format
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