A bias-correction method for closed-loop identification of Linear Parameter-Varying systems

Automatica ◽  
2018 ◽  
Vol 87 ◽  
pp. 128-141 ◽  
Author(s):  
Manas Mejari ◽  
Dario Piga ◽  
Alberto Bemporad
Keyword(s):  
Bias Correction ◽  
Closed Loop ◽  
Correction Method ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Linear Parameter Varying Systems ◽  
Bias Correction Method ◽  
Closed Loop Identification ◽  
Parameter Varying

On the fractional closed-loop linear parameter varying system identification under noise corrupted scheduling and output signal measurements

2019 ◽  
Vol 41 (10) ◽  
pp. 2909-2921
Author(s):  
Zaineb Yakoub ◽  
Messaoud Amairi ◽  
Mohamed Aoun ◽  
Manel Chetoui
Keyword(s):  
Closed Loop ◽  
Industrial Process ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Linear Parameter Varying Systems ◽  
Performance Constraints ◽  
Instrumental Variable Method ◽  
Parameter Varying ◽  
And Performance ◽  
Linear Parameter Varying System

It is well known that, in some industrial process identification situations, measurements can be collected from closed-loop experiments for several reasons such as stability, safety, and performance constraints. In this paper, we investigate the problem of identifying continuous-time fractional closed-loop linear parameter varying systems. The simplified refined instrumental variable method is developed to estimate both coefficients and differentiation orders. This method is established to provide consistent estimates when the output and the scheduling variable are contaminated by additive measurements noise. The proposed scheme is evaluated in comparison with other approaches in terms of a simulation example.

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