Special Issue on Applications to Control, Signals,
CO-EDITORS: J. GARLOFF and
Much of modern engineering theory addresses problems involving uncertainty.
E.g., in control theory, a typical scenario begins with a system to be controlled and
a mathematical model of this system which depends on uncertain quantities. This
model thus involvesvarious physical parameters whose values may be speciﬁed only
within given bounds. Besides these data uncertainties, the designer is faced with
another difﬁculty: Many problems require a yes/no answer, e.g., stable/unstable.
Even when an algorithm designed to solve such a problem can ﬁnd the correct result
using real arithmetic, it may fail to do so due to rounding errors when implemented
on a computer using ﬂoating point arithmetic.
Interval methods appear as an appropriate tool to cope with data uncertainties as well
as with rounding errors. However, designers are often confronted with a nonlinear
uncertainty structure which makes the problem considerably more difﬁcult. E.g.,
after massaging the study of the stability of some uncertain system into a polynomial
problem with coefﬁcients depending on uncertain parameters, these parameters
generally enter into more than one coefﬁcient of the polynomial, and in many
cases, these coefﬁcients depend nonlinearly on the uncertain parameters. In addition
to the traditional domain of afﬁne and multiafﬁne uncertainty structure, recent
advances have opened up potential new application areas for reliable methods in
communications, control, signal processing, and related ﬁelds. The application-
oriented special issue of Reliable Computing is intended to provide a forum for the
presentation of advances in using reliable methods in these areas.
Contributions for this special issue should be sent as L
X ﬁle and as hard copy to
both of the following Guest Editors before July 31, 1998:
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