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Pragmatic Design Methods Using Adaptive Controller Structures for Mechatronic Applications with Variable Parameters and Working Conditions

  • Stefan PreitlEmail author
  • Radu-Emil Precup
  • Zsuzsa Preitl
  • Alexandra-Iulia Stînean
  • Claudia-Adina Dragoş
  • Mircea-Bogdan Rădac
Chapter
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 55)

Abstract

This chapter treats two pragmatic design methods for controllers dedicated to mechatronic applications working under variable conditions; for such applications adaptive structures of the control algorithms are of great interest. Basically, the design is based on two extensions of the modulus optimum method and of the symmetrical optimum method (SO-m): the Extended SO-m and the double parameterization of the SO-m (2p-SO-m). Both methods are introduced by the authors and they use PI(D) controllers that can ensure high control performance: increased value of the phase margins, improved tracking performance, and efficient disturbance rejection. A short and systematic presentation of the methods and digital implementation aspects using an adaptive structure of the algorithms for industrial applications are given. The application deals with a cascade speed control structure for a driving system with continuously variable parameters, i.e., electrical drives with variable reference input, variable moment of inertia and variable disturbance input.

Keywords

Fuzzy Controller Controller Parameter Phase Margin Variable Reference Load Disturbance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

List of Abbreviations

SO-m

Symmetrical Optimum method

Mo-M

Modulus Optimum method

ESO-m

Extended Symmetrical Optimum method

2p-SO-m

Double parameterization of the SO-m

2-DOF

Two Degree of Freedom

VMI

Variable Moment of Inertia

t.f.

Transfer function

c.a.

Control algorithm

C-VR-MI-LD

Continuously Variable Reference, Moment of Inertia and Load Disturbance

DC-m, BLDC-m

DC-motors, Brush-Less DC-motors

MM

Mathematical Model

CS

Control Structure

CCS

Cascade Control Structure

Notes

Acknowledgments

This work was supported by a grant in the framework of the Partnerships in priority areas—PN II program of the Romanian National Authority for Scientific Research ANCS, CNDI - UEFISCDI, project number PN-II-PT-PCCA-2011-3.2-0732, by a grant of the Romanian National Authority for Scientific Research, CNCS - UEFISCDI, project number PN-II-ID-PCE-2011-3-0109. Also, the work was partially supported by the strategic grant POSDRU ID 77265 (2010) of the Ministry of Labor, Family and Social Protection, Romania, co-financed by the European Social Fund—Investing in People.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Stefan Preitl
    • 1
    Email author
  • Radu-Emil Precup
    • 1
  • Zsuzsa Preitl
    • 2
  • Alexandra-Iulia Stînean
    • 1
  • Claudia-Adina Dragoş
    • 1
  • Mircea-Bogdan Rădac
    • 1
  1. 1.Department of Automation and Applied Informatics“Politehnica” University of TimisoaraTimisoaraRomania
  2. 2.Siemens A.G.ErlangenGermany

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