Worst-case experiment design for constrained MISO systems
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Date
2014
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Conference Paper
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yes
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Abstract
The problem of optimal worst-case experiment design for constrained linear systems with multiple inputs represented by a parametric model is addressed. A theoretical result is derived, which provides an insight on how to design experiments that minimize the worst-case identification error in ∞- and 1-norm when the input constraints are symmetric. The presented result is valid for a general model parametrization that admits the commonly used finite impulse response model as a special case. Based on this result a computationally tractable algorithm for the worst-case experiment design is proposed. Its advantages over a more standard experiment design approach are illustrated in a numerical example.
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2014 IEEE 53rd Annual Conference on Decision and Control (CDC 2014)
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999 - 1004
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IEEE
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53rd IEEE Annual Conference on Decision and Control (CDC 2014)
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03416 - Morari, Manfred (emeritus)