Title :
Controllability and stabilizability of probabilistic logical control networks
Author :
Yin Zhao ; Daizhan Cheng
Author_Institution :
Key Lab. of Syst. & Control, AMSS, Beijing, China
Abstract :
Necessary and sufficient conditions of controllability and stabilizability of probabilistic Boolean control networks are first introduced, by using the controllability matrix of switched Boolean control networks. Then, these results are generalized to mix-valued logical control networks, which include the Boolean control networks as a special case. The algebraic forms of mix-valued logical control networks and Boolean networks make this generalization very natural. Finally, using the input-state incidence matrix of higher-order logical control networks, the results are also extended to higher-order case.
Keywords :
Boolean functions; controllability; matrix algebra; probability; stability; algebraic forms; controllability conditions; controllability matrix; higher-order logical control networks; input-state incidence matrix; mix-valued logical control networks; probabilistic Boolean control networks; probabilistic logical control networks; stabilizability conditions; switched Boolean control networks; Artificial neural networks; Boolean functions; Controllability; Mathematical model; Probabilistic logic; Vectors;
Conference_Titel :
Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
Conference_Location :
Maui, HI
Print_ISBN :
978-1-4673-2065-8
Electronic_ISBN :
0743-1546
DOI :
10.1109/CDC.2012.6427395