Disturbance observer structure based internal model control for time delay systems

2015 ◽  
Author(s):  
Sudeshna Dasgupta ◽  
Smita Sadhu ◽  
T.K. Ghoshal
Keyword(s):  
Time Delay ◽  
Internal Model ◽  
Disturbance Observer ◽  
Internal Model Control ◽  
Delay Systems ◽  
Time Delay Systems ◽  
Model Control

Internal model control for a class of uncertain time-delay systems

2016 ◽  
Author(s):  
Saeed Salavati Dezfuli ◽  
Behrouz Ebrahimi ◽  
Karolos Grigoriadis ◽  
Matthew Franchek
Keyword(s):  
Time Delay ◽  
Internal Model ◽  
Internal Model Control ◽  
Delay Systems ◽  
Time Delay Systems ◽  
Model Control ◽  
Uncertain Time

scholarly journals Approximation Methods for FO-IMC Controllers for Time Delay Systems

2019 ◽  
Vol 115 ◽  
pp. 01003
Author(s):  
Cristina I. Muresan ◽  
Isabela R. Birs ◽  
Ovidiu Prodan ◽  
Ioan Nascu ◽  
Robin De Keyser
Keyword(s):  
Time Delay ◽  
Fractional Order ◽  
Approximation Method ◽  
Closed Loop ◽  
Internal Model Control ◽  
Delay Systems ◽  
Order System ◽  
Test Cases ◽  
Time Delay Systems ◽  
Model Control

Fractional Order Internal Model Control (FO-IMC) is among the newest trends in extending fractional calculus to the integer order control. Approximation of the FO-IMC is one of the key problems. Apart from this, when dealing with time delay systems, the time delay needs also to be approximated. All these approximations can alter the closed loop performance of the controller. In this paper, FO-IMC controllers will be tested in terms of the approximation accuracy. The case study is a first order system with time delay. Several scenarios will be considered, aiming for a conclusion regarding the choice of the approximation method as a function of the process characteristics, closed loop performance and FO-IMC fractional order. To approximate the time delay, two extensively used techniques will be considered, such as the series and Pade approximations. These will be compared to a novel approximation technique. An analysis of the test cases presented show that the series approximation proves more suitable in a single scenario, whereas the novel approximation method produces better results for the rest of the test cases.

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