Distributed non-linear robust consensus-based sensor calibration for networked control systems

2020 ◽  
Vol 14 (9) ◽  
pp. 1200-1208
Author(s):  
Maja S. Stanković ◽  
Dragan S. Antić
Keyword(s):  
Control Systems ◽  
Networked Control Systems ◽  
Networked Control ◽  
Sensor Calibration ◽  
Non Linear ◽  
Robust Consensus

A New Congestion Controller for Multilayer Networked Control Systems with Persistent Disturbances

2010 ◽  
Vol 439-440 ◽  
pp. 805-810 ◽  
Author(s):  
Peng Liu
Keyword(s):  
Control Systems ◽  
Networked Control Systems ◽  
Feedforward Control ◽  
Initial Conditions ◽  
Optimal Solution ◽  
Networked Control ◽  
Suboptimal Control ◽  
Control Law ◽  
Non Linear ◽  
Persistent Disturbances

In this paper, a new congestion controller is developed to obtain a feedforward and feedback optimal control for networked control systems (NCS) with persistent disturbances. The disturbances have known dynamic characteristics but unknown initial conditions. The disturbance observer is proposed to make the feedforward control law realizable physically. In the approach only the non-linear compensating term, solution of a sequence of adjoint vector differential equations, is required iteration. By taking the finite iteration of non-linear compensating term of optimal solution sequence, a suboptimal control law for NCS with time delay can be obtained.

scholarly journals Fuzzy control with estimated variable sampling period for non-linear networked control systems: 2-DOF helicopter as case study

2011 ◽  
Vol 34 (7) ◽  
pp. 802-814 ◽  
Author(s):  
PE Méndez-Monroy ◽  
H Benítez-Pérez
Keyword(s):  
Control Systems ◽  
Fuzzy Controller ◽  
Networked Control Systems ◽  
Sampling Period ◽  
Networked Control ◽  
System Stability ◽  
Control Input ◽  
Variable Sampling ◽  
Wide Range ◽  
Non Linear

This paper presents a fuzzy controller for class of non-linear networked control systems; the varying time delays and packet loss are taken as a variable sampling period of the system. The variable sampling period is estimated using a time stamped and probability density function. A fuzzy model smoothly switches to estimate the system state; the antecedent input is the estimated sampling period and the consequent part is formed by linear models discretized with specific sampling periods. The fuzzy controller generates a control input using the estimated states to ensure system stability for a wide range of sampling periods. A two-degree-of-freedom helicopter is used to show the applicability and effectiveness of the controller with robustness to traffic.

Observer design for classes of non-linear networked control systems

2012 ◽  
Vol 15 (2) ◽  
pp. 108 ◽  
Author(s):  
Romain Postoyan ◽  
Tarek Ahmed Ali ◽  
N.A. Franç ◽  
oise Lamnabhi Lagarrigue
Keyword(s):  
Control Systems ◽  
Networked Control Systems ◽  
Observer Design ◽  
Networked Control ◽  
Non Linear
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