Controller validation
type: Item
instance of: scholarly article
title: Controller validation
zbMATH Open document ID: 1007.93023
author: T. F. Brozenec
author: T. C. Tsao
author: Michael G. Safonov
published in: International Journal of Adaptive Control and Signal Processing
publication date: 2003-03-20T00:00:00Z
Mathematics Subject Classification ID: 93B30
Mathematics Subject Classification ID: 93B35
zbMATH DE Number: 1691394
zbMATH Keywords: robust controllers
zbMATH Keywords: controller validation
zbMATH Keywords: controller unfalsification
zbMATH Keywords: closed-loop controller performance
zbMATH Keywords: model validation
MaRDI profile type: Publication
full work available at URL: acs.683
OpenAlex ID: W4249792873
cites work: Control oriented system identification: a worst-case/deterministic approach in H/sub infinity /
cites work: Set-membership identification of systems with parametric and nonparametric uncertainty
cites work: Quantifying the error in estimated transfer functions with application to model order selection
cites work: Model validation: a connection between robust control and identification
cites work: A time-domain approach to model validation
cites work: Paradigms and puzzles in the theory of dynamical systems
cites work: Q4764177
cites work: The unfalsified control concept and learning
cites work: On the -Boundedness of Solutions of Nonlinear Functional Equations
cites work: A Frequency-Domain Condition for the Stability of Feedback Systems Containing a Single Time-Varying Nonlinear Element
cites work: Q4273823
DOI: 10.1002/ACS.683
review text: This paper is concerned with controller validation or, as otherwise called, controller unfalsification. The study of the unfalsified control provides a theoretical basis for directly validating closed-loop controller performance from open-loop experimental data, or even from closed-loop data obtained during the use of another controller in the feedback loop. The paper expands this theory through a study of the connections between model and controller validation. It is shown that controller validation is a feedback generalization of model validation and that it is less conservative to unfalsify (validate) control laws directly rather than unfalsify (validate) the plant models from which those control laws are constructed. The approach of the paper allows controller validation to be accomplished without making any prior assumptions about the plant or the noise. Thus the conservatism inherent in indirect two-step validation approaches that require one to first identify a plant model and uncertainty bounds from experimental data before analyzing control system robustness is avoided.
reviewed by: Spyros G. Tzafestas
description: scientific article; zbMATH DE number 1691394