Accelerated quantitative feedback theory interval automatic loop shaping algorithm

Martínez Forte, Isaac; Cervera López, Joaquín

Publication:
Accelerated quantitative feedback theory interval automatic loop shaping algorithm

dc.contributor.author	Martínez Forte, Isaac
dc.contributor.author	Cervera López, Joaquín
dc.contributor.department	Informática y Sistemas
dc.date.accessioned	2022-09-08T14:29:40Z
dc.date.available	2022-09-08T14:29:40Z
dc.date.issued	2021-03-24
dc.description.abstract	The quest for an efficient quantitative feedback theory (QFT) Automatic Loop Shaping algorithm is an open research problem. Different approaches have been adopted in the literature to efficiently solve this optimization problem, which is computationally hard due to its nonlinear and nonconvex nature. The first algorithms focused on different forms of simplification of the original problem, leading to faster but not accurate results. Stochastic algorithms have been another popular way of dealing with the complexity of this problem. These algorithms are faster than an exhaustive search, but do not guarantee, in general, the globally optimal solution. A third, more recent, approach, consists of using interval analysis global search algorithms, which are able to accurately solve the original problem, and are very suitable for execution speed optimization. In this work, one of these algorithms is taken as a basis to propose and develop an improved algorithm which is more efficient in terms of the execution time needed to solve a given problem. This improved efficiency is achieved by using two new information sources: Phase information and feasible boxes information. The main contribution of this work is to propose the use of these two new information sources to reduce execution time and to integrate this idea in the original algorithm. Their individual and joint associated speedups are measured by solving two classical QFT example problems: Matlab® QFT Toolbox example 2 and ACC ’90 benchmark problem. The results show that the new algorithm’s performance is significantly better.	es
dc.format	application/pdf	es
dc.format.extent	19	es
dc.identifier.citation	International Journal of Robust and Nonlinear Control, 31, 9, Pag. 4378– 4396,
dc.identifier.doi	https://doi.org/10.1002/rnc.5499
dc.identifier.issn	1049-8923
dc.identifier.issn	1099-1239
dc.identifier.uri	http://hdl.handle.net/10201/123363
dc.language	eng	es
dc.relation	Sin financiación externa a la Universidad	es
dc.relation.publisherversion	https://onlinelibrary.wiley.com/doi/abs/10.1002/rnc.5499	es
dc.rights	info:eu-repo/semantics/openAccess	es
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/	*
dc.subject	automatic loop shaping	es
dc.subject	CACSD	es
dc.subject	control design	es
dc.subject	interval optimization	es
dc.subject	quantitative feedback theory	es
dc.subject	robust control	es
dc.subject	uncertain systems	es
dc.subject.other	CDU::0 - Generalidades.::00 - Ciencia y conocimiento. Investigación. Cultura. Humanidades.::004 - Ciencia y tecnología de los ordenadores. Informática.	es
dc.title	Accelerated quantitative feedback theory interval automatic loop shaping algorithm	es
dc.type	info:eu-repo/semantics/article	es
dspace.entity.type	Publication	es