Discrete-time dynamic average consensus

Automatica ◽  
2010 ◽  
Vol 46 (2) ◽  
pp. 322-329 ◽  
Author(s):  
Minghui Zhu ◽  
Sonia Martínez
Keyword(s):  
Discrete Time ◽  
Time Dynamic ◽  
Average Consensus

Step size analysis in discrete-time dynamic average consensus

2014 ◽  
Author(s):  
Eduardo Montijano ◽  
Juan I. Montijano ◽  
Carlos Sagues ◽  
Sonia Martinez
Keyword(s):  
Discrete Time ◽  
Size Analysis ◽  
Step Size ◽  
Time Dynamic ◽  
Average Consensus

Robust discrete time dynamic average consensus

Automatica ◽  
2014 ◽  
Vol 50 (12) ◽  
pp. 3131-3138 ◽  
Author(s):  
Eduardo Montijano ◽  
Juan Ignacio Montijano ◽  
Carlos Sagüés ◽  
Sonia Martínez
Keyword(s):  
Discrete Time ◽  
Time Dynamic ◽  
Average Consensus

scholarly journals Search for a moving target in a competitive environment

2021 ◽  
Author(s):  
Benoit Duvocelle ◽  
János Flesch ◽  
Hui Min Shi ◽  
Dries Vermeulen
Keyword(s):  
Markov Chain ◽  
Discrete Time ◽  
Competitive Environment ◽  
Moving Target ◽  
Time Varying ◽  
Greedy Strategy ◽  
Time Dynamic ◽  
Dynamic Search ◽  
Subgame Perfect Equilibria ◽  
Perfect Equilibria

AbstractWe consider a discrete-time dynamic search game in which a number of players compete to find an invisible object that is moving according to a time-varying Markov chain. We examine the subgame perfect equilibria of these games. The main result of the paper is that the set of subgame perfect equilibria is exactly the set of greedy strategy profiles, i.e. those strategy profiles in which the players always choose an action that maximizes their probability of immediately finding the object. We discuss various variations and extensions of the model.

Discrete-Time Robust Control of Linear Periodically Time-Varying Systems

2007 ◽  
Author(s):  
S. Kalender ◽  
H. Flashner
Keyword(s):  
Robust Control ◽  
Discrete Time ◽  
Robustness Analysis ◽  
Value Theory ◽  
Time Varying ◽  
Sampled Data ◽  
Point Mapping ◽  
Time Dynamic ◽  
Time Representation ◽  
Time Varying Systems

An approach for robust control of periodically time-varying systems is proposed. The approach combines the point-mapping formulation and a parameterization of the control vector to formulate an equivalent time-invariant discrete-time representation of the system. The discrete-time representation of the dynamic system allows for the application of known sampled-data control design methodologies. A perturbed, discrete-time dynamic model is formulated and plant parametric uncertainty are obtained using a truncated point-mapping algorithm. The error bounds due to point-mapping approximation are computed and a robustness analysis problem of the system due to parametric uncertainties is formulated using structured singular value theory. The proposed approach is illustrated by two design examples. Simulation studies show good performance robustness of the control system to parameter perturbations and system nonlinearities.

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