Publication result detail

Advanced Robust PDC Fuzzy Control of Nonlinear Systems

M. Polanský

Original Title

Advanced Robust PDC Fuzzy Control of Nonlinear Systems

English Title

Advanced Robust PDC Fuzzy Control of Nonlinear Systems

Type

Peer-reviewed article not indexed in WoS or Scopus

Original Abstract

This paper introduces a new method called ARPDC (Advanced Robust Parallel Distributed Compensation) for automatic control of nonlinear systems. This method improves a quality of robust control by interpolating of robust and optimal controller. The weight of each controller is determined by an original criteria function for model validity and disturbance appreciation. ARPDC method is based on nonlinear Takagi-Sugeno (T-S) fuzzy systems and Parallel Distributed Compensation (PDC) control scheme. The relaxed stability conditions of ARPDC control of nominal system have been derived. The advantages of presented method are demonstrated on the inverse pendulum benchmark problem. From comparison between three different controllers (robust, optimal and ARPDC) follows, that ARPDC control is almost optimal with the robustness close to the robust controller. The results indicate that ARPDC algorithm can be a good alternative not only for a robust control, but in some cases also to an adaptive control of nonlinear systems.

English abstract

This paper introduces a new method called ARPDC (Advanced Robust Parallel Distributed Compensation) for automatic control of nonlinear systems. This method improves a quality of robust control by interpolating of robust and optimal controller. The weight of each controller is determined by an original criteria function for model validity and disturbance appreciation. ARPDC method is based on nonlinear Takagi-Sugeno (T-S) fuzzy systems and Parallel Distributed Compensation (PDC) control scheme. The relaxed stability conditions of ARPDC control of nominal system have been derived. The advantages of presented method are demonstrated on the inverse pendulum benchmark problem. From comparison between three different controllers (robust, optimal and ARPDC) follows, that ARPDC control is almost optimal with the robustness close to the robust controller. The results indicate that ARPDC algorithm can be a good alternative not only for a robust control, but in some cases also to an adaptive control of nonlinear systems.

Keywords

Robust control, optimal control, Takagi–Sugeno (TS) fuzzy models, linear matrix inequality (LMI), observer, Advanced Robust Parallel Distributed Compensation (ARPDC)

Key words in English

Robust control, optimal control, Takagi–Sugeno (TS) fuzzy models, linear matrix inequality (LMI), observer, Advanced Robust Parallel Distributed Compensation (ARPDC)

Authors

M. Polanský

Released

01.03.2006

ISBN

1305-5313

Periodical

Transactions on Engineering, Computing and Technology

Volume

2006

Number

v11

State

Republic of Turkey

Pages from

177

Pages count

6

BibTex

@article{BUT43617,
  author="Michal {Polanský}",
  title="Advanced Robust PDC Fuzzy Control of Nonlinear Systems",
  journal="Transactions on Engineering, Computing and Technology",
  year="2006",
  volume="2006",
  number="v11",
  pages="6",
  issn="1305-5313"
}