Stabilization of Discrete-Time Markovian Jump Systems via Controllers with Partially Mode-Dependent Characterization

Abstract

A kind of stabilizing controller in terms of being partially mode-dependent is developed for discrete-time Markovian jump systems (MJSs). The property referred to be partially mode-dependent is described by the Bernoulli variable. Based on the established model, the stabilization for MJSs over unreliable networks is considered, where both network-induced delay and packet dropout take place in system modes and states. Such effects of network are taken into account in controller design. All the conditions are derived in terms of linear matrix inequalities (LMIs). Finally, illustrative examples are presented to show the effectiveness and applicability of the proposed method.

Performance Accretion in Delay Compensation of Networked Control System Using Markov Approach-Based Randomness Estimation in Smith Predictor

“…Various experiments have performed using Markov chain to design LQG optimal controller and the random delays unveiled in NCS have been validated (Bhuyan et. al., 2012;Zhai et. al., 2013).…”

An Improved Lag-Time Compensation Technique in Distributed Networked Control System based on Smith Predictor

“…The closed loop in equation ( 7) is a markov jump linear system with two markov chains that describe the behavior of the system for s-c time delays and packet dropouts respectively. This enables to analyze and synthesize such NCS by applying markov jump linear system and help us to estimate the modified state space model of the plant [30,31]. The Markov approach estimates the uncertain feedback delay and compares for estimated disturbance ep (t), which modify the disturbance variables for the predicted process.…”