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Observer Design for Control and Fault Diagnosis of Boolean Networks (Paperback, 1st ed. 2022)
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Observer Design for Control and Fault Diagnosis of Boolean Networks (Paperback, 1st ed. 2022)
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Boolean control networks (BCNs) are a kind of parameter-free model,
which can be used to approximate the qualitative behavior of
biological systems. After converting into a model similar to the
standard discrete-time state-space model, control-theoretic
problems of BCNs can be studied. In control theory, state observers
can provide state estimation for any other applications.
Reconstructibility condition is necessary for the existence of
state observers. In this thesis explicit and recursive methods have
been developed for reconstructibility analysis. Then, an approach
to design Luenberger-like observer has been proposed, which works
in a two-step process (i.e. predict and update). If a BCN is
reconstructible, then an accurate state estimate can be provided by
the observer no later than the minimal reconstructibility index.
For a wide range of applications the approach has been extended to
enable design of unknown input observer, distributed observers and
reduced-order observer. The performance of the observers has been
evaluated thoroughly. Furthermore, methods for output tracking
control and fault diagnosis of BCNs have been developed. Finally,
the developed schemes are tested with numerical examples.
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