DocumentCode :
3601633
Title :
Networked Control With Stochastic Scheduling
Author :
Kun Liu ; Fridman, Emilia ; Johansson, Karl Henrik
Author_Institution :
ACCESS Linnaeus Centre & Sch. of Electr. Eng., KTH R. Inst. of Technol., Stockholm, Sweden
Volume :
60
Issue :
11
fYear :
2015
Firstpage :
3071
Lastpage :
3076
Abstract :
This note develops the time-delay approach to networked control systems with scheduling protocols, variable delays and variable sampling intervals. The scheduling of sensor communication is defined by a stochastic protocol. Two classes of protocols are considered. The first one is defined by an independent and identically-distributed stochastic process. The activation probability of each sensor node for this protocol is a given constant, whereas it is assumed that collisions occur with a certain probability. The resulting closed-loop system is a stochastic impulsive system with delays both in the continuous dynamics and in the reset equations, where the system matrices have stochastic parameters with Bernoulli distributions. The second scheduling protocol is defined by a discrete-time Markov chain with a known transition probability matrix taking into account collisions. The resulting closed-loop system is a Markovian jump impulsive system with delays both in the continuous dynamics and in the reset equations. Sufficient conditions for exponential mean-square stability of the resulting closed-loop system are derived via a Lyapunov-Krasovskii-based method. The efficiency of the method is illustrated on an example of a batch reactor. It is demonstrated how the time-delay approach allows treating network-induced delays larger than the sampling intervals in the presence of collisions.
Keywords :
Lyapunov methods; Markov processes; closed loop systems; delays; discrete time systems; matrix algebra; networked control systems; protocols; sampling methods; scheduling; statistical distributions; Bernoulli distribution; Lyapunov-Krasovskii-based method; Markovian jump impulsive system; NCS; activation probability; closed-loop system; discrete-time Markov chain; networked control system; sampling interval; sensor communication; stochastic impulsive system; stochastic process; stochastic scheduling protocol; time-delay approach; transition probability matrix; Actuators; Closed loop systems; Delays; Mathematical model; Protocols; Stability analysis; Stochastic processes; Lyapunov functional; Networked control systems; Stochastic impulsive system; Stochastic protocols; networked control systems; stochastic impulsive system; stochastic protocols;
fLanguage :
English
Journal_Title :
Automatic Control, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9286
Type :
jour
DOI :
10.1109/TAC.2015.2414812
Filename :
7063933
Link To Document :
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