Abstract
Recently, Mao (2013) discusses the mean-square exponential stabilization of continuous-time hybrid stochastic differential equations by feedback controls based on discrete-time state observations. Mao (2013) also obtains an upper bound on the duration τ between two consecutive state observations. However, it is due to the general technique used there that the bound on τ is not very sharp. In this paper, we will consider a couple of important classes of hybrid SDEs. Making full use of their special features, we will be able to establish a better bound on τ . Our new theory enables us to observe the system state less frequently (so costs less) but still to be able to design the feedback control based on the discrete-time state observations to stabilize the given hybrid SDEs in the sense of mean-square exponential stability.
Original language | English |
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Pages (from-to) | 88-95 |
Number of pages | 8 |
Journal | Systems and Control Letters |
Volume | 73 |
Early online date | 20 Sept 2014 |
DOIs | |
Publication status | Published - Nov 2014 |
Keywords
- Brownian motion
- Markov chain
- mean-square exponential stability
- feedback control
- discrete-time state observation
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ASYMPTOTIC STABILITY OF NEURAL-TYPE STOCHASTIC FUNCTIONAL DIFFERENTIAL EQUATIONS
Mao, X. (Principal Investigator)
EPSRC (Engineering and Physical Sciences Research Council)
Project: Research