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    Exact Tuning of PID Controllers in Control Feedback Design

    165271_165271.pdf (387.3Kb)
    Access Status
    Open access
    Authors
    Ntogramatzidis, Lorenzo
    Ferrante, A.
    Date
    2011
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Ntogramatzidis, Lorenzo and Ferrante, Augusto. 2011. Exact tuning of PID controllers in control feedback design. IET Control Theory and Applications. 5 (4): pp. 565-578.
    Source Title
    IET Control Theory and Applications
    DOI
    10.1049/iet-cta.2010.0239
    ISSN
    17518644
    School
    Department of Mathematics and Statistics
    Remarks

    © 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works..

    URI
    http://hdl.handle.net/20.500.11937/11873
    Collection
    • Curtin Research Publications
    Abstract

    In this study, the authors introduce a range of techniques for the exact design of PID controllers for feedback control problems involving requirements on the steady-state performance and standard frequency-domain specifications on the stability margins and crossover frequencies. These techniques hinge on a set of simple closed-form formulae for the explicit computation of the parameters of the controller in finite terms as functions of the specifications, and therefore they eliminate the need for graphical, heuristic or trial-and-error procedures. The relevance of this approach is (i) theoretical, since a closed-form solution is provided for the design of PID-type controllers with standard frequency-domain specifications; (ii) computational, since the techniques presented here are readily implementable as software routines, for example, using MATLAB®; (iii) educational, because the synthesis of the controller reduces to a simple exercise on complex numbers that can be solved with pen, paper and a scientific calculator. These techniques also appear to be very convenient within the context of adaptive control and self-tuning strategies, where the controller parameters have to be calculated online. Furthermore, they can be easily combined with graphical and first/second-order plant approximation methods in the cases where the model of the system to be controlled is not known.

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