Abstract
This paper deals with the problems of stability and stabilization of a networked brushless DC motor (BLDCM) in the presence of random delay. At first, sensor-to-controller random delay is modeled as a Markov chain, and the resulting closed-loop system is transformed to a Markovian jump linear system (MJLS). The transition probabilities of MJLSs are partly unknown due to the complexity of network. Sufficient conditions for stochastic stability and stabilization of the underlying systems are derived via a new linear matrix inequalities (LMIs) formulation. Then, the stabilizing output feedback controller design is achieved by assuming some elements in the transition probability matrix (TPM) to be unknown or unavailable. Numerical simulations are carried out to demonstrate the effectiveness of the designed controller.
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