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Abstract
This paper introduces a novel method to control linear parameter varying (LPV) systems by employing methodologies and algorithms for deployment of - generally known as - fractional order controllers (FOC). The origin of FOC stems from fractional calculus where arbitrary order dynamic characterising functions can be used as envelop for varying dynamic properties of systems. The main feature employed here is the property of robustness, an intrinsic characteristic of FOC, if tuned accordingly. We present here the rationale and method for injecting a high degree of robustness for LPV dynamic systems. A study case from aerospace engineering is used to illustrate the proposed method and to demonstrate its usefulness. The realistic simulation results indicate that the proposed scheme works well and fulfils the imposed specifications.
Keywords
FRACTIONAL PID CONTROLLERS, INTEGRAL RESONANT CONTROL, SPECIAL-ISSUE, ROBUST-CONTROL, DESIGN

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MLA
Ionescu, Clara-Mihaela, et al. “Control of LPV Mechatronic Systems in Presence of Dynamic Uncertainties.” 2017 IEEE 21ST INTERNATIONAL CONFERENCE ON INTELLIGENT ENGINEERING SYSTEMS (INES), 2017, pp. 125–30.
APA
Ionescu, C.-M., Van Oevelen, N., Copot, D., Paijmans, B., & De Keyser, R. (2017). Control of LPV mechatronic systems in presence of dynamic uncertainties. 2017 IEEE 21ST INTERNATIONAL CONFERENCE ON INTELLIGENT ENGINEERING SYSTEMS (INES), 125–130. Oct 20-23, 2017.
Chicago author-date
Ionescu, Clara-Mihaela, Nicolas Van Oevelen, Dana Copot, Bart Paijmans, and Robain De Keyser. 2017. “Control of LPV Mechatronic Systems in Presence of Dynamic Uncertainties.” In 2017 IEEE 21ST INTERNATIONAL CONFERENCE ON INTELLIGENT ENGINEERING SYSTEMS (INES), 125–30. Oct 20-23, 2017.
Chicago author-date (all authors)
Ionescu, Clara-Mihaela, Nicolas Van Oevelen, Dana Copot, Bart Paijmans, and Robain De Keyser. 2017. “Control of LPV Mechatronic Systems in Presence of Dynamic Uncertainties.” In 2017 IEEE 21ST INTERNATIONAL CONFERENCE ON INTELLIGENT ENGINEERING SYSTEMS (INES), 125–130. Oct 20-23, 2017.
Vancouver
1.
Ionescu C-M, Van Oevelen N, Copot D, Paijmans B, De Keyser R. Control of LPV mechatronic systems in presence of dynamic uncertainties. In: 2017 IEEE 21ST INTERNATIONAL CONFERENCE ON INTELLIGENT ENGINEERING SYSTEMS (INES). Oct 20-23, 2017; 2017. p. 125–30.
IEEE
[1]
C.-M. Ionescu, N. Van Oevelen, D. Copot, B. Paijmans, and R. De Keyser, “Control of LPV mechatronic systems in presence of dynamic uncertainties,” in 2017 IEEE 21ST INTERNATIONAL CONFERENCE ON INTELLIGENT ENGINEERING SYSTEMS (INES), Larnaca, CYPRUS, 2017, pp. 125–130.
@inproceedings{8544421,
  abstract     = {{This paper introduces a novel method to control linear parameter varying (LPV) systems by employing methodologies and algorithms for deployment of - generally known as - fractional order controllers (FOC). The origin of FOC stems from fractional calculus where arbitrary order dynamic characterising functions can be used as envelop for varying dynamic properties of systems. The main feature employed here is the property of robustness, an intrinsic characteristic of FOC, if tuned accordingly. We present here the rationale and method for injecting a high degree of robustness for LPV dynamic systems. A study case from aerospace engineering is used to illustrate the proposed method and to demonstrate its usefulness. The realistic simulation results indicate that the proposed scheme works well and fulfils the imposed specifications.}},
  author       = {{Ionescu, Clara-Mihaela and Van Oevelen, Nicolas and Copot, Dana and Paijmans, Bart and De Keyser, Robain}},
  booktitle    = {{2017 IEEE 21ST INTERNATIONAL CONFERENCE ON INTELLIGENT ENGINEERING SYSTEMS (INES)}},
  isbn         = {{978-1-4799-7677-5}},
  issn         = {{1562-5850}},
  keywords     = {{FRACTIONAL PID CONTROLLERS,INTEGRAL RESONANT CONTROL,SPECIAL-ISSUE,ROBUST-CONTROL,DESIGN}},
  language     = {{eng}},
  location     = {{Larnaca, CYPRUS}},
  pages        = {{125--130}},
  title        = {{Control of LPV mechatronic systems in presence of dynamic uncertainties}},
  year         = {{2017}},
}

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