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On the convergence of the Prediction Error Method to its global minimum

Eckhard, Diego (author)
Bazanella, Alexandre S. (author)
Rojas, Cristian R., 1980- (author)
KTH,Reglerteknik,ACCESS Linnaeus Centre,System Identification Group
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Hjalmarsson, Håkan, 1962- (author)
KTH,Reglerteknik,ACCESS Linnaeus Centre,System Identification Group
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 (creator_code:org_t)
IFAC, 2012
2012
English.
In: 16th IFAC Symposium on System Identification. - : IFAC. - 9783902823069 ; , s. 698-703
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • The Prediction Error Method (PEM) is related to an optimization problem built on input/output data collected from the system to be identified. It is often hard to find the global solution of this optimization problem because the corresponding objective function presents local minima and/or the search space is constrained to a nonconvex set. The existence of local minima, and hence the difficulty in solving the optimization, depends mainly on the experimental conditions, more specifically on the spectrum of the input/output data collected from the system. It is therefore possible to avoid the existence of local minima by properly choosing the spectrum of the input; in this paper we show how to perform this choice. We present sufficient conditions for the convergence of PEM to the global minimum and from these conditions we derive two approaches to avoid the existence of nonglobal minima. We present the application of one of these two approaches to a case study where standard identification toolboxes tend to get trapped in nonglobal minima.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)

Keyword

Convergence
Gradient methods
Identification

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