Title :
Gain estimates and exponential ISS for a class of hybrid dynamical networks
Author :
Bin Liu ; Chunxia Dou ; Dong-Nan Liu
Author_Institution :
Coll. of Sci., Hunan Univ. of Technol., Zhuzhou, China
fDate :
May 31 2014-June 2 2014
Abstract :
This paper studies the exponential input-to-state stability (e-ISS) for hybrid dynamical networks (HDNs) consisting of flow and jumping subsystems. Concepts of input-to-state exponent (IS-E) and event-ISS are proposed. By using the IS-E estimates of subsystems and the method of multiple Lyapunov functions and M-matrix theory, the e-ISS including event-e-ISS criteria are established for HDNs. The small-gain condition for the coupling of flows is needed while such condition for the coupling of impulses is not necessary. It also shows that a HDN may have ISS even all subsystems have no ISS. Finally, one example is given to illustrate the results.
Keywords :
Lyapunov methods; asymptotic stability; input-output stability; matrix algebra; HDN; IS-E estimates; Lyapunov functions; M-matrix theory; event-e-ISS criteria; exponential ISS; exponential input-to-state stability; flow coupling; flow subsystems; gain estimates; hybrid dynamical networks; input-to-state exponent; jumping subsystems; small-gain condition; Couplings; Educational institutions; Lyapunov methods; Silicon; Stability criteria; Switches; Input-to-state stability (ISS); M-matrix; hybrid dynamical network; multiple Lyapunov functions;
Conference_Titel :
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-3707-3
DOI :
10.1109/CCDC.2014.6852307