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PID Tuning (A Modern Approach via the Weighted Sensitivity Problem)

List Price: $65.99
SKU:
9780367536909
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  • Product Details

    Author:
    Salvador Alcántara Cano, Ramon Vilanova Arbós, Carles Pedret i Ferré
    Format:
    Paperback
    Pages:
    154
    Publisher:
    CRC Press (September 25, 2023)
    Language:
    English
    ISBN-13:
    9780367536909
    Weight:
    16oz
    Dimensions:
    7" x 10"
    File:
    TAYLORFRANCIS-TayFran_260513043736269-20260513.xml
    Folder:
    TAYLORFRANCIS
    List Price:
    $65.99
    Case Pack:
    1
    As low as:
    $62.69
    Publisher Identifier:
    P-CRC
    Discount Code:
    H
    Country of Origin:
    United States
    Pub Discount:
    30
    Imprint:
    CRC Press
  • Overview

    The PID controller is the most common option in the realm of control applications and is dominant in the process control industry. Among the related analytical methods, Internal Model Control (IMC) has gained remarkable industrial acceptance due to its robust nature and good set-point responses. However, the traditional application of IMC results in poor load disturbance rejection for lag-dominant and integrating plants. This book presents an IMC-like design method which avoids this common pitfall and is devised to work well for plants of modest complexity, for which analytical PID tuning is plausible. For simplicity, the design only focuses on the closed-loop sensitivity function, including formulations for the H and H2 norms. Aimed at graduate students and researchers in control engineering, this book:

    • Considers both the robustness/performance and the servo/regulation trade-offs
    • Presents a systematic, optimization-based approach, ultimately leading to well-motivated, model-based, and analytically derived tuning rules
    • Shows how to tune PID controllers in a unified way, encompassing stable, integrating, and unstable processes
    • Finds in the Weighted Sensitivity Problem the sweet spot of robust, optimal, and PID control
    • Provides a common analytical framework that generalizes existing tuning proposals