Non-fragile control design for stochastic Markov jump system with multiple delays and cyber attacks

2021 ◽  
Author(s):  
H. Divya ◽  
R. Sakthivel ◽  
S.A. Karthick ◽  
C. Aouiti
Keyword(s):  
Control Design ◽  
Cyber Attacks ◽  
Multiple Delays ◽  
Markov Jump ◽  
Markov Jump System

scholarly journals Hybrid Event-Triggered Filtering for Nonlinear Markov Jump Systems With Stochastic Cyber-Attacks

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 248-258
Author(s):  
Wenqian Xie ◽  
Yong Zeng ◽  
Kaibo Shi ◽  
Xin Wang ◽  
Qianhua Fu
Keyword(s):  
Cyber Attacks ◽  
Markov Jump ◽  
Markov Jump Systems ◽  
Jump Systems ◽  
Event Triggered ◽  
Hybrid Event

FEEDBACK PREDICTIVE CONTROL OF NONHOMOGENEOUS MARKOV JUMP SYSTEMS WITH NONSYMMETRIC CONSTRAINTS

2014 ◽  
Vol 56 (2) ◽  
pp. 138-149
Author(s):  
YANQING LIU ◽  
FEI LIU
Keyword(s):  
Predictive Control ◽  
Controller Design ◽  
Invariant Set ◽  
Markov Jump ◽  
Markov Jump Systems ◽  
Markov Jump System ◽  
Predictive Controller ◽  
Feasibility Region ◽  
Nonhomogeneous Markov Jump System ◽  
Jump Systems

AbstractWe consider feedback predictive control of a discrete nonhomogeneous Markov jump system with nonsymmetric constraints. The probability transition of the Markov chain is modelled as a time-varying polytope. An ellipsoid set is utilized to construct an invariant set in the predictive controller design. However, when the constraints are nonsymmetric, this method leads to results which are over conserved due to the geometric characteristics of the ellipsoid set. Thus, a polyhedral invariant set is applied to enlarge the initial feasible area. The results obtained are for a more general class of dynamical systems, and the feasibility region is significantly enlarged. A numerical example is presented to illustrate the advantage of the proposed method.

scholarly journals A Simplified Predictive Control of Constrained Markov Jump System with Mixed Uncertainties

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Yanyan Yin ◽  
Yanqing Liu ◽  
Hamid R. Karimi
Keyword(s):  
Predictive Control ◽  
Transition Probability ◽  
Dynamic Performance ◽  
Markov Jump ◽  
Markov Jump System ◽  
Predictive Controller ◽  
Model Predictive Control Algorithm ◽  
Simplified Algorithm ◽  
Jump Systems ◽  
Mixed Uncertainties

A simplified model predictive control algorithm is designed for discrete-time Markov jump systems with mixed uncertainties. The mixed uncertainties include model polytope uncertainty and partly unknown transition probability. The simplified algorithm involves finite steps. Firstly, in the previous steps, a simplified mode-dependent predictive controller is presented to drive the state to the neighbor area around the origin. Then the trajectory of states is driven as expected to the origin by the final-step mode-independent predictive controller. The computational burden is dramatically cut down and thus it costs less time but has the acceptable dynamic performance. Furthermore, the polyhedron invariant set is utilized to enlarge the initial feasible area. The numerical example is provided to illustrate the efficiency of the developed results.

Proportional integral observer based tracking control design for Markov jump systems

2021 ◽  
Vol 410 ◽  
pp. 126467
Author(s):  
M. Vijayakumar ◽  
R. Sakthivel ◽  
Ardashir Mohammadzadeh ◽  
S.A. Karthick ◽  
S. Marshal Anthoni
Keyword(s):  
Tracking Control ◽  
Control Design ◽  
Markov Jump ◽  
Markov Jump Systems ◽  
Proportional Integral ◽  
Jump Systems
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