Mean Square Exponential Stabilization of Sampled-Data Systems Subject to Actuator Nonlinearities, Random Sampling and Packet Dropouts

This work deals with the mean square exponential stabilization of sampled-data linear systems subject to sector-bounded actuator nonlinearities and to aperiodic sampling intervals, which are assumed to be Erlang-distributed random variables. The possibility of packet dropouts is also taken into acco...

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Bibliographic Details
Published inIEEE transactions on automatic control Vol. 69; no. 2; pp. 1 - 8
Main Authors Huff, Daniel Denardi, Fiacchini, Mirko, Silva, Joao Manoel Gomes da
Format Journal Article
LanguageEnglish
Published New York IEEE 01.02.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Actuators
Control systems design
Data systems
Exponential distribution
Feedback control
Hybrid systems
Linear matrix inequalities
Linear systems
Markov processes
Nonlinearity
Piecewise deterministic markov processes
Random sampling
Random variables
Sampled data systems
sampled-data control
sector-bounded nonlinearities
Stabilization
State feedback
Symmetric matrices
Uncertainty
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Summary:This work deals with the mean square exponential stabilization of sampled-data linear systems subject to sector-bounded actuator nonlinearities and to aperiodic sampling intervals, which are assumed to be Erlang-distributed random variables. The possibility of packet dropouts is also taken into account and modeled by a Bernoulli process. Linear Matrix Inequality (LMI) conditions are proposed to design a stabilizing state-feedback controller for the system. Moreover, it is shown that the method leads to necessary and sufficient stabilization conditions in the absence of actuator nonlinearities. The results are derived using the framework of Piecewise Deterministic Markov Processes, a subclass of stochastic hybrid systems.
ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2023.3300970