- Conference Paper
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. Show more
Book title2014 IEEE 53rd Annual Conference on Decision and Control (CDC 2014)
Pages / Article No.
Organisational unit03416 - Morari, Manfred (emeritus)
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