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Books > Science & Mathematics > Mathematics > Algebra
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Outliers in Control Engineering - Fractional Calculus Perspective (Hardcover)
Loot Price: R3,949
Discovery Miles 39 490
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Outliers in Control Engineering - Fractional Calculus Perspective (Hardcover)
Series: Fractional Calculus in Applied Sciences and Engineering
Supplier out of stock. If you add this item to your wish list we will let you know when it becomes available.
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Outliers play an important, though underestimated, role in control
engineering. Traditionally they are unseen and neglected. In
opposition, industrial practice gives frequent examples of their
existence and their mostly negative impacts on the control quality.
The origin of outliers is never fully known. Some of them are
generated externally to the process (exogenous), like for instance
erroneous observations, data corrupted by control systems or the
effect of human intervention. Such outliers appear occasionally
with some unknow probability shifting real value often to some
strange and nonsense value. They are frequently called deviants,
anomalies or contaminants. In most cases we are interested in their
detection and removal. However, there exists the second kind of
outliers. Quite often strange looking data observations are not
artificial data occurrences. They may be just representatives of
the underlying generation mechanism being inseparable internal part
of the process (endogenous outliers). In such a case they are not
wrong and should be treated with cautiousness, as they may include
important information about the dynamic nature of the process. As
such they cannot be neglected nor simply removed. The Outlier
should be detected, labelled and suitably treated. These activities
cannot be performed without proper analytical tools and modeling
approaches. There are dozens of methods proposed by scientists,
starting from Gaussian-based statistical scoring up to data mining
artificial intelligence tools. The research presented in this book
presents novel approach incorporating non-Gaussian statistical
tools and fractional calculus approach revealing new data analytics
applied to this important and challenging task. The proposed book
includes a collection of contributions addressing different yet
cohesive subjects, like dynamic modelling, classical control,
advanced control, fractional calculus, statistical analytics
focused on an ultimate goal: robust and outlier-proof analysis. All
studied problems show that outliers play an important role and
classical methods, in which outlier are not taken into account, do
not give good results. Applications from different engineering
areas are considered such as semiconductor process control and
monitoring, MIMO peltier temperature control and health monitoring,
networked control systems, and etc.
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