Output selection and observer design for boolean control networks: A sub-optimal polynomial-complexity algorithm

Eyal Weiss; Michael Margaliot

doi:10.1109/LCSYS.2018.2872295

Output selection and observer design for boolean control networks: A sub-optimal polynomial-complexity algorithm

Eyal Weiss, Michael Margaliot^*

^*Corresponding author for this work

School of Electrical Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

We derive a new graph-theoretic sufficient condition for observability of a Boolean control network (BCN). We describe two algorithms that are based on this condition. The first selects a set of nodes so that observing this set makes the BCN observable. The second algorithm builds an observer for the observable BCN. Both algorithms are sub-optimal, as they are based on a sufficient but not necessary condition for observability. Yet their time-complexity is linear in the length of the description of the BCN, rendering them feasible for largescale BCNs. We discuss how these results can be used to provide a sub-optimal yet polynomial-complexity algorithm for the minimal observability problem in BCNs. Some of the theoretical results are demonstrated using BCN models of mammalian cell cycle control, and T-cell receptor kinetics.

Original language	English
Article number	8474357
Pages (from-to)	210-215
Number of pages	6
Journal	IEEE Control Systems Letters
Volume	3
Issue number	1
DOIs	https://doi.org/10.1109/LCSYS.2018.2872295
State	Published - Jan 2019

Keywords

Boolean control networks and logic networks
observers for nonlinear systems
systems biology.

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10.1109/LCSYS.2018.2872295

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abstract = "We derive a new graph-theoretic sufficient condition for observability of a Boolean control network (BCN). We describe two algorithms that are based on this condition. The first selects a set of nodes so that observing this set makes the BCN observable. The second algorithm builds an observer for the observable BCN. Both algorithms are sub-optimal, as they are based on a sufficient but not necessary condition for observability. Yet their time-complexity is linear in the length of the description of the BCN, rendering them feasible for largescale BCNs. We discuss how these results can be used to provide a sub-optimal yet polynomial-complexity algorithm for the minimal observability problem in BCNs. Some of the theoretical results are demonstrated using BCN models of mammalian cell cycle control, and T-cell receptor kinetics.",

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Output selection and observer design for boolean control networks: A sub-optimal polynomial-complexity algorithm

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