Experimental validation of the discrete-time MCS adaptive strategy

Mario Di Bernardo; Alessandro Di Gaeta; Umberto Montanaro; Josep M. Olm; Stefania Santini

doi:10.1016/j.conengprac.2012.12.004

Experimental validation of the discrete-time MCS adaptive strategy

Mario Di Bernardo, Alessandro Di Gaeta, Umberto Montanaro^*, Josep M. Olm, Stefania Santini

^*Corresponding author for this work

University of Bristol

Research output: Contribution to journal › Article (Academic Journal) › peer-review

21 Citations (Scopus)

Abstract

This paper is concerned with the implementation and experimental validation of a discrete-time model reference adaptive control strategy, known as Minimal Control Synthesis (MCS) algorithm. After discussing the proof of stability of the algorithm when applied to discretized models of continuous-time plants, the problem of controlling a highly nonlinear electro-mechanical device is taken as a representative case of study. It is shown that the discrete-time MCS is an effective strategy to solve the problem while guaranteeing robustness to unmodeled nonlinear dynamics over a wide range of test manoeuvres.

Original language	English
Pages (from-to)	847-859
Number of pages	13
Journal	Control Engineering Practice
Volume	21
Issue number	6
DOIs	https://doi.org/10.1016/j.conengprac.2012.12.004
Publication status	Published - 1 Jun 2013

Research Groups and Themes

Engineering Mathematics Research Group
Bristol BioDesign Institute

Keywords

Adaptive systems
synthetic biology
Validation
Discrete time systems
Adaptive algorithms
Model reference adaptive control

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title = "Experimental validation of the discrete-time MCS adaptive strategy",

abstract = "This paper is concerned with the implementation and experimental validation of a discrete-time model reference adaptive control strategy, known as Minimal Control Synthesis (MCS) algorithm. After discussing the proof of stability of the algorithm when applied to discretized models of continuous-time plants, the problem of controlling a highly nonlinear electro-mechanical device is taken as a representative case of study. It is shown that the discrete-time MCS is an effective strategy to solve the problem while guaranteeing robustness to unmodeled nonlinear dynamics over a wide range of test manoeuvres.",

keywords = "Adaptive systems, synthetic biology, Validation, Discrete time systems, Adaptive algorithms, Model reference adaptive control",

author = "\{Di Bernardo\}, Mario and \{Di Gaeta\}, Alessandro and Umberto Montanaro and Olm, \{Josep M.\} and Stefania Santini",

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doi = "10.1016/j.conengprac.2012.12.004",

language = "English",

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T1 - Experimental validation of the discrete-time MCS adaptive strategy

AU - Di Bernardo, Mario

AU - Di Gaeta, Alessandro

AU - Montanaro, Umberto

AU - Olm, Josep M.

AU - Santini, Stefania

PY - 2013/6/1

Y1 - 2013/6/1

N2 - This paper is concerned with the implementation and experimental validation of a discrete-time model reference adaptive control strategy, known as Minimal Control Synthesis (MCS) algorithm. After discussing the proof of stability of the algorithm when applied to discretized models of continuous-time plants, the problem of controlling a highly nonlinear electro-mechanical device is taken as a representative case of study. It is shown that the discrete-time MCS is an effective strategy to solve the problem while guaranteeing robustness to unmodeled nonlinear dynamics over a wide range of test manoeuvres.

AB - This paper is concerned with the implementation and experimental validation of a discrete-time model reference adaptive control strategy, known as Minimal Control Synthesis (MCS) algorithm. After discussing the proof of stability of the algorithm when applied to discretized models of continuous-time plants, the problem of controlling a highly nonlinear electro-mechanical device is taken as a representative case of study. It is shown that the discrete-time MCS is an effective strategy to solve the problem while guaranteeing robustness to unmodeled nonlinear dynamics over a wide range of test manoeuvres.

KW - Adaptive systems

KW - synthetic biology

KW - Validation

KW - Discrete time systems

KW - Adaptive algorithms

KW - Model reference adaptive control

UR - https://www.scopus.com/pages/publications/84875937959

U2 - 10.1016/j.conengprac.2012.12.004

DO - 10.1016/j.conengprac.2012.12.004

M3 - Article (Academic Journal)

AN - SCOPUS:84875937959

SN - 0967-0661

VL - 21

SP - 847

EP - 859

JO - Control Engineering Practice

JF - Control Engineering Practice

IS - 6

ER -

Experimental validation of the discrete-time MCS adaptive strategy

Abstract

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Keywords

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