Digital Controller Design using State Space Methods

2020 ◽  
pp. 131-176
Author(s):  
Gregory Starr
Keyword(s):  
State Space ◽  
Controller Design ◽  
Digital Controller ◽  
State Space Methods

scholarly journals Forecasting Bordeaux wine prices using state-space methods

2018 ◽  
Vol 50 (47) ◽  
pp. 5110-5121 ◽  
Author(s):  
Stephen Bazen ◽  
Jean-Marie Cardebat
Keyword(s):  
State Space ◽  
State Space Methods

Single and three phase moving average filter PLLs: Digital controller design recipe

2014 ◽  
Vol 116 ◽  
pp. 276-283 ◽  
Author(s):  
Naji Rajai Nasri Ama ◽  
Wilson Komatsu ◽  
Lourenco Matakas Junior
Keyword(s):  
Controller Design ◽  
Moving Average ◽  
Digital Controller ◽  
Moving Average Filter ◽  
Three Phase ◽  
Average Filter

Digital Controller Design for Half-Car Active Suspension System with Using Singular Perturbation Theory

2011 ◽  
Vol 403-408 ◽  
pp. 4800-4805 ◽  
Author(s):  
A. R. Paarya ◽  
H. Zarabadipour
Keyword(s):  
Perturbation Theory ◽  
Controller Design ◽  
Suspension System ◽  
Digital Controller ◽  
Singular Perturbation Theory ◽  
Vehicle Suspension ◽  
Car Model ◽  
Perturbed Systems ◽  
Simulation Results ◽  
Vehicle Suspension System

In this paper the digital controller design for vehicle suspension system, based on a half-car model using singular perturbed systems is considered. This strategy is based on the slow and fast subsystems controller design. The simulation results show them favorable performance of the controller and achieve fast and good response.

Stewart Platform Model with Uncertain Parameters

2010 ◽  
Vol 164 ◽  
pp. 177-182 ◽  
Author(s):  
Lukas Březina ◽  
Tomáš Březina
Keyword(s):  
State Space ◽  
Controller Design ◽  
State Space Model ◽  
Stewart Platform ◽  
Dynamics Model ◽  
H Infinity ◽  
Uncertain Dynamics ◽  
Six Dof ◽  
Linear State ◽  
Nominal Position

The paper deals with development of uncertain dynamics model of a six DOF parallel mechanism (Stewart platform) suitable for H-infinity controller design. The model is based on linear state space models of the machine obtained by linearization of the SimMechanics model. The linearization is performed for two positions of the machine in its workspace. It is the nominal position and the position where each link of the machine reaches its maximal length. The uncertainties are then represented as differences between parameters of corresponding state-space matrices. The uncertain state space model is then obtained using upper linear fractional transformation. There are also mentioned several notes regarding H-infinity controller designed according to the obtained model.

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