Gradient approximations in iterative feedback tuning for multivariable processes
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
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.
adaptive control, controller tuning, multivariable systems, optimization
Research subject SRA - ICT
IdentifiersURN: urn:nbn:se:kth:diva-23846DOI: 10.1002/acs.826ISI: 000224791900005ScopusID: 2-s2.0-6344256926OAI: oai:DiVA.org:kth-23846DiVA: diva2:342545
QC 20100525 QC 20110922 QC 201507242010-08-102010-08-102015-07-24Bibliographically approved